BR112020012749B1 - PROCESS AND SYSTEM FOR MANAGING A PLURALITY OF MIXING PROJECTS IN A MIXING PROJECT CATALOG OF A CONCRETE PRODUCER, AND PROCESS FOR CREATING A NEW CONCRETE MIXING PROJECT - Google Patents

Abstract

This is an exemplary process and system for managing a concrete producer's mix design catalog that involves collecting slump curve data obtained during in-transit monitoring of delivered concrete loads produced from a plurality of mix designs. mixing, where each mixing design is identified by a different identification code (regardless of the fact that the components are different), group slump curve data that have the same movement characteristics according to the assigned resistance value, and select a mix design to produce, to display, or both to produce and to display, from among two or more individual mix design slump data curves within the same data curve cluster. Selection is based on the same movement characteristic and assigned strength value, and at least one factor regarding cost, performance, physical appearance, quality or other characteristic of the concrete mix or its components. Exemplary methods for generating new mixture designs are also disclosed.

Description

FIELD OF THE INVENTION

[001] The invention relates to the field of hydratable cementitious materials, and more particularly to the management of the mixing project catalog of a concrete producer, based on the identification of groupings of slump curve data obtained during the monitoring of delivery of concrete in transit from individual concrete loads produced from various mix designs, and classification of each grouping of curves based on selection factors as desired by the concrete producer.

BACKGROUND OF THE INVENTION

[002] Concrete producers, such as ready-mixed or precast concrete manufacturers, require different concrete mix designs to meet strength and slump targets for various customers and to address various applications (e.g., floors, columns) . Typically, the design of a concrete mix takes into account several factors including the type of cement, type and ratio of aggregate, water to cement (w/c) ratio, chemical addition mix (or mixes), air characteristics, placement methods and various other factors.

[003] The term “mixing design catalog”, as used in this document, refers to the collection or accumulation of various concrete mixing designs from a given concrete producer. Concrete producers quickly accumulate concrete mixing projects in their catalogs over time. In the construction industry, successful concrete producers typically have an extended track record in the business. During customer base expansion or production plant acquisition, for example, a concrete producer can rapidly increase its number of product offerings from tens to hundreds, and from hundreds to thousands, and even tens of thousands. The ratio of significantly different and useful mix designs can vary widely. That is, for many concrete producers, there could be a large number of duplicate mix designs, meaning that several designs could be effectively dropped from the mix design catalogue. As will be explained, however, cleaning can be a heavy burden for the concrete producer and often does not occur in the concrete industry.

[004] Concrete producers collect concrete mix designs over time for various reasons. Such reasons include, as an example, different construction applications that require different aggregates, different aggregate mixes or different mixing ratios (e.g. coarse to fine aggregate), different amounts of water depending on aggregate packages (See, for e.g. ACI 211-65), and different add-on mixing components (e.g. air entrainers, corrosion inhibitors, plasticizers, etc.).

[005] Various concrete mix designs may also arise due to a large number of technical or performance considerations and specific customer requirements. For example, material sources and raw materials change over time. These can include cements, pozzolans, aggregates, chemical addition mixes and other components. Component replacement may involve new mixing ratios. All these considerations give rise to new mixing designs.

[006] A safety team or quality control department can generate new mix designs to satisfy individual customer requests. Placing new mix design codes on “new” mix designs may involve minor changes to the actual component mix. this could result in negligible differences in quality or performance between two different mixture designs.

[007] The present inventors believe that over time the mixing design catalog increases in size due to the fact that old mixing designs are retained in the catalog even as new mixing designs are added. As a new mix design often requires laboratory or large-scale testing to confirm performance, producers are hesitant to remove mix designs from their catalogs. This is partly due to the desire to avoid wasting past investments in testing the mix design, as well as the consideration that past mix design performance may be required or required for a future design.

[008] However, it is due to the rapidly increasing number of mix designs that concrete producers are increasingly finding it to confirm that an existing mix design will meet the specific requirements of a future customer. This is especially true if a change occurs to a material that is required in a large portion of the blend projects within the blend catalog. The very act of reassessing a multitude of existing blending designs means that a great deal of time can be required to analyze a collection of blending designs to confirm that a specific desired performance can be achieved by a given blending design within the collection. The growing number of blending projects impedes capacity, as well as precluding the assignment of a QA group to manage the blending project catalog. In other words, the large number of blending projects leads to a limited ability to verify performance through physical testing as the effort is spread across the many blending projects. This dilutes the quality of information for any mixing design that leads to oversizing as required by standards such as ACI 318-14. Thus, the present inventors believe that the very proliferation of mix designs is, in itself, a significant cost increase for concrete producers.

[009] Although there are methods to create new mix designs that include the ACI mix design method (ACI 211.1-91), methods developed by Ken Day (Concrete Mix Design, Quality Control and Specification), methods developed by Francois de Larrard (Concrete Mixture Proportioning), and Per Andersen ((see, for example, U.S. Patent No. 7,386,368, where the use of a "K-factor" is disclosed to generate new mix designs), there are currently no methods to manage the various mix projects that a concrete producer has accumulated in its mix design catalog over time, based on real-time rheology monitoring processes.

[010] Consequently, the present inventors believe that the concrete industry needs an innovative and inventive way to efficiently and effectively manage a concrete producer's mix project catalog.

SUMMARY OF THE INVENTION

[011] Addressing the problem of constantly expanding mixing design catalogs of concrete producers, the present invention facilitates the ability of a concrete producer to organize, manage and select a mixing design from within a mixing design catalog. highly populated concrete mix and, ultimately, reduce the number of necessary mix designs considered to meet the given design requirements, thereby concentrating information per given mix design, eventually leading to less oversizing.

[012] The invention provides both a process and a system that can be implemented, using monitoring devices and components that are commercially available in the concrete industry, according to the teachings, as should be particularly described in this document.

[013] An exemplary process of the invention for managing a plurality of mixing projects in the mixing design catalog of a concrete producer, comprises: collecting slump curve data obtained during the monitoring of individual concrete loads produced from a plurality of mixing designs, in which each mixing design is identified by a different identification code regardless of whether the mixing components are different or identical; grouping (or pooling) slump curve data having the same motion characteristics into at least two slump curve data groupings; associate each mix design within the slump curve data cluster with an assigned strength value; and selecting a mix design to produce, to display, or both to produce and to display, from among the two or more individual mix designs within the same slump curve data cluster, the selection being based on the same value of assigned strength and at least one selection factor chosen from among cost, performance, physical appearance, quality or combination thereof.

[014] An exemplary system of the invention for managing a plurality of mixing projects in the mixing project catalog of a concrete producer, comprises: a plurality of ready-mix concrete delivery trucks, each having a processing unit for computer (CPU) communicative with a first sensor or sensors for measuring the energy associated with the rotation of a load of concrete mix within a rotating mixing drum (e.g., such as hydraulic pressure sensors, strain gauge or strain gauge type sensors , etc.) and communicative with a second sensor for measuring the speed of rotation of the mixing drum (for example, an accelerometer), in which the CPUs are programmed to store in the memory accessible by the CPU, a plurality of slump data curves obtained during in-transit delivery monitoring of individual concrete loads produced from a plurality of mix designs (as identified by mix design number or individual identification code, irrespective of whether their mix components are identical or different) ; and a computer processing unit that is programmed (the computer processor is a chip, circuit, machine, hardware, etc., in the truck, remote location, for example, so-called cloud-based system that is not necessarily in the truck or control center location): (a) gather (e.g. collate) the slump curve data that has been obtained during and from in-transit delivery monitoring of individual concrete loads produced from a plurality of construction projects mix (as identified by mix design number or individual identification code, regardless of whether your mix components are identical or different) according to assigned strength values; and (b) selecting, displaying, or both selecting and displaying a preferred mix design chosen from a pool of a plurality of slump curve data at a given assigned strength value, based on at least one selection factor (for (e.g. mix or total mix component costs, cement type, aggregate type, addition mix type, w/c and many other possible selection factors).

[015] In exemplary embodiments of the invention, the selection factor can be chosen from cost, performance, property or physical characteristic, or other considerations. Examples of selection factors might include (a) mix design material cost; (b) material cost of any of the blending components; (c) number of past deliveries; (d) total volume delivered from a particular concrete mix project; (e) number of available stress test results; (f) shipment approval statuses; (g) source of materials used in the concrete mix; (h) a characteristic or property of an aggregate material used in the blending project; (i) a hydration characteristic or property of the cement used in the mix design; (j) a packing density characteristic or property within the concrete mix; (k) a characteristic or property of the durability or reactive nature of the concrete mix; (I) a characteristic or property of placing the concrete mix; (m) chemical addition mixture used in mixing concrete; (n) air characteristic of concrete; (o) diameter of the hose or pipe used to transport the concrete from the delivery truck, mixer or pump to the placement site at the construction site; or (p) a combination of any of the aforementioned factors.

[016] Initially, the concrete producer can assign a strength value to a given concrete mix using any number of available methods. Typically, when a new mix design is produced, using, for example, ACI 211.1-91, conservative estimates for the w/c can be used to arrive at a strength. For example, a 28-day strength of 41.37 MPa (6,000 psi) can be achieved with an a/c of 0.41 for a concrete mix with no air drag, subjected to an actual physically produced test mix, produced to ensure correct properties such as slump and strength. According to standards such as ACI 318-14, to achieve design strength (to satisfy the structural requirements of concrete), it is necessary to strive for higher strength averages. This is based on production variability and because of this inherent variability (which can be reduced with tighter quality control), the mix design needs to be oversized to ensure that the design strength is met on a statistically acceptable basis. Often, in blend designs, design strength is designed, and for examples of this invention, it can be a means of assigning strength criteria. Other factors can help assign strengths, for example the grower may initially start with using the a/c pattern as an indication of strength value. There are more sophisticated resistance methods. The producer can alternatively use the methods of Anderson et al. in U.S. Patent No. 7,386,368, where strength, slump, and cost are estimated using a "K factor" that involves considering the influence of plant materials on concrete strength, although the present inventors suspect that this process can be taxing as material sources change over time.

[017] The present inventors unexpectedly discovered that mixing designs could exist with vastly different mixing constituents, but which could surprisingly share the same rheological characteristics, and vice versa, that mixing designs with apparently similar mixing constituents could have different motion behavior (e.g. culling). The present invention provides a process for managing highly populated mix design catalogs that have a high number of superfluous mix designs; and it provides several advantages, as described in the following paragraph.

[018] QA managers will be able to reduce hundreds and possibly thousands of blending projects down to perhaps twenty or thirty blending projects. This will facilitate quality control, allowing managers to focus on varying fewer mix designs, and perhaps more quickly identify the causes of variances. Fewer mixing projects means that the concrete producer has spent more time per mixing project, thereby providing greater volumes of information per mixing design and therefore accuracy in terms of slump monitoring as well as strength testing; or, in other words, the producer can thereby more quickly obtain information about how concrete mixes perform on a more statistically significant basis. This can result in avoiding oversizing a mix (eg adding extra cement to ensure strength requirements are met), and allowing the producer to optimize a mix design without, for example, spending money on extra cement.

[019] The invention also provides exemplary methods for generating new concrete mix designs based on information obtained from, such as interpolated from, an existing mix design catalog containing rheology information and strength values, and real or empirically derived based on existing mixing designs. For example, a process for creating a new concrete mix design, comprising: collecting slump curve data obtained while monitoring individual concrete loads produced from a plurality of concrete mix designs, where each design concrete mix corresponds to a different identification code regardless of whether the mix components are different or identical; grouping slump curve data having the same motion characteristics into at least two slump curve data groupings; associate each mix design within the slump curve data cluster with an assigned strength value; enter a target strength and rheology; interpolate mix design components based on at least two existing mix designs where strength and rheology targets are satisfied; and creating a new mix project to produce, display, or both produce and display, based on mix design components interpolated from the at least two existing mix designs.

[020] The advantages additional features of the invention are discussed hereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

[021] An evaluation of the benefits and features of the invention can be more readily understood when the following written description of the preferred embodiments is considered in conjunction with the drawings as described in the following paragraphs.

[022] Figure 1 is a graphic illustration of an automated concrete monitoring process, in which the energy (for example, hydraulic pressure in terms of pounds per square inch, measured along the left vertical axis) associated with the rotation of a load of concrete mix within a rotating mixing drum is monitored at different drum speeds (e.g. revolutions per minute or “rpm” as indicated on the right vertical axis) over time (when measured in hours:minutes as indicated on the horizontal axis).

[023] Figure 2 is a graphical illustration of curves representing energy (eg, hydraulic pressure) and slump data values corresponding to five different concrete mix designs, as monitored at a constant drum rotation speed.

[024] Figure 3 is a schematic illustration that suggests that the multiplicative number of "slump ladder" calibrations that may be required for a ready-mix concrete plant depends on which concrete producer may need to deliver loads of concrete produced from various mix types (ie groups of mix designs that have, for example, similar water or cement contents) and several different mixer truck types.

[025] Figure 4 is a graphical illustration of drum pressure/speed, as monitored over time, where the solid line illustrates hydraulic pressure (psi) and the dotted line illustrates drum speed (rpm), and where elapsed time is designated along the horizontal axis.

[026] Figure 5 is a graphic illustration of various curves corresponding to various concrete mixes from different mix designs that were monitored for slump (vertical axis) and hydraulic pressure (horizontal axis) at drum speed.

[027] Figure 6 is a graphical illustration of data curves generated by measuring slump (vertical axis) in relation to hydraulic pressure (horizontal axis) for six different mixing designs at a drum speed, where the two different mixture designs at the bottom of the graph are seen to define the same slump/pressure curve behavior and thus are assumed to move in the same way and thus can be brought together or compiled as a “grouping” of data curves for purposes of reducing the number of concrete mix designs, which may be accomplished using one or more selection factors as taught in accordance with the present invention.

[028] Figure 7 is a three-dimensional histogram in which 608 total mixing designs are mapped according to the mixing design number (indicated along the left vertical axis) that belongs to a grouping of slump curves (as assigned along the left horizontal axis) and that has an assigned resistance value (as indicated along the rightmost horizontal axis).

[029] Figure 8 is a two-dimensional graph derived from the three-dimensional histogram of Figure 7 in which the 608 total mixing designs can be reduced to 37 different total mixing designs that have the same slump curve behavior (same grouping) in the values assigned resistance.

[030] Figure 9 is a flow chart illustrating various steps within an exemplary process of the present invention.

[031] Figure 10 is a two-dimensional graph illustrating an exemplary method of the invention to interpolate a new concrete mix design based on information from an existing concrete mix catalog.

DESCRIPTION OF EXAMPLE MODALITIES A. DEFINITIONS

[032] The term “concrete” refers to a mixture of cement (which often contains supplementary cementitious materials such as limestone, fly ash, granulated blast furnace slag and other pozzolanic materials) and aggregates (e.g. fine aggregate , such as sand, coarse aggregate, such as gravel) and, optionally, one or more chemical addition mixtures (e.g. plasticizers to increase workability, cure accelerators, cure retarders, air entrainers, air retainers, mixes by addition of plastic shrinkage reducers, corrosion inhibitors (for rebar) to modify concrete in its plastic or hardened state. hardening reaction.

[033] The term "cement" includes hydratable cement, such as Portland cement that is produced by pulverizing clinker consisting of hydraulic calcium silicates, aluminates and aluminoferrites, and one or more forms of calcium sulfate (for example, natural gypsum ) as an intermediate additive. Typically, Portland cement is combined with one or more supplemental cementitious materials, such as fly ash, granulated blast furnace slag, limestone, natural pozzolans or mixtures thereof, and supplied as a blend, all of which bind the aggregates together. to produce concrete.

[034] The term "aggregate" means and refers to particles of sand and stone, typically having an average particle size of 0.5 to 50 mm. Aggregates may also comprise calciferous or siliceous limestone minerals. Such aggregates can be of the “natural” type (for example, derived from glacial, alluvial or marine deposits which are typically weathered so that the particles have smooth surfaces) or they can be of the “manufactured” type, which are produced using of mechanical crushers or grinding devices. Coarse aggregate stone particles are typically grouped into various size fractions, as described, for example, in ASTM C33-16e. As the size fraction used is controlled by many factors, including but not limited to the spacing between rebars in a proposed construction, aggregate size is often a major consideration in the design of a concrete mix. Aggregates can also mean and refer to lightweight aggregates such as expanded shale, pumice, sintered fly ash or other low density fillers.

[035] The terms “concrete mix design”, “mix design” and “mix ratio” refer to the ingredients and proportions of ingredients used to produce a given concrete that has one or more desired properties, either in a state plastic, hardened state, or both. The concrete mix is often designed based on many factors, such as, for example, cement type, aggregate type, w/c ratio, chemical addition mix, air characteristic and other factors or ingredients. These and various other “selection factors” will be discussed further below as a general discussion of how various concrete mixes from a concrete producer mix design catalog are monitored for slump curve data.

[036] The term “mix design catalog” refers generally to a collection, compilation or repository of various mix designs within the control of a concrete producer and which is accessible by a computer processor. This may refer to one or more electronic files or folders, including cloud storage locations or across various computer device or computer processor systems, under the control of and subject to access by the concrete producer.

[037] Mixing projects are designated by a “mixing code” or symbol that is an identifier for particular proportions of ingredients. A set of ingredient ratios can have different mix codes. Furthermore, a mix code within a given producer's collection of mix codes may refer to different ratios of ingredients. This case arises when the same basic mix design is used in different concrete plants owned or controlled by a single concrete producer. Due to the fact that each individual concrete plant may source materials from different locations (eg aggregates from different local quarries), ingredient proportions may vary slightly.

[038] The proportions of mix design components (e.g., cement, aggregate, water, optional addition mixes) may be expressed as amounts of material per volume of concrete (e.g., 611 pounds of cement per cubic yard of concrete (362.5 kg/m3)). Ratios can also be expressed as fractions or percentages (eg, 0.09 kg (3 oz) of superplasticizer addition mix per 45.36 kg (100 lbs) of cement). Concrete components are often described in terms of types: such as cement, supplementary cementitious materials, aggregates (fine, coarse, or both), water, and addition mixes. Components can be individually characterized in terms of type or source.

[039] For example, if more than one source of a particular material exists for a producer, the mix design may indicate the particular type (for example, ASTM Type 1 cement versus ASTM Type III cement, or ASTM C33 stone No. 57 versus stone ASTM C33 No. 7), or source (eg, coarse aggregate that is mined from a river bed versus coarse aggregate that is crushed from a quarry).

[040] Additional information can be included in the mixture design, along with the proportions of ingredients, such as, for example, target performance values. These performance values could be a design strength (e.g. 28 day strength), a target slump or slump range, a target air content or air range, a target or durability range (e.g. shrinkage, fluency, etc.), etc.

[041] The term “assigned resistance” refers to a resistance value associated with a particular mixture design. The concrete producer typically assigns a number that corresponds to the compressive strength value (usually in units of pounds per inch or PSI) as obtained from empirical testing of cylinder specimens produced in accordance with standards such as ACI 211.191 and ACI 318-14. While ACI 211.1-91 designates a design strength (i.e. strength to satisfy structural requirements), an average required strength is designated by ACI 318-14, where this value takes into account both design strength and design variability mixture produced. Thus, the required average strength includes an oversizing of the design strength to ensure that the design strength is met on a statistically acceptable basis. The assigned resistance value or number can be chosen to be the design resistance or the required average resistance. Alternatively, the concrete producer can assign a strength number based on a/c, cement content, packing fraction or other factors.

[042] The term “slump curve data”, as used in this document refers to the data necessary to predict slump or other rheological parameters, such as elastic limit, viscosity, thixotropy, etc., based on sensor readings that monitor mixing vessels, such as a mixing drum on a concrete truck or stationary mixer in a precast concrete plant. Different applications may require different rheology considerations (eg lower viscosity for pumping through hoses). Examples of sensor readings include mixer drum rotation, energy required to rotate the drum, force on an internal probe in the mixer, and more. The slump curve data allows prediction of slump based on movement of concrete within the mixer and therefore provides a description of movement of concrete within the mixer.

[043] The term “slump” as used in this document shall refer to the workability property of concrete, as determined using the conventional vertical drop measurement of concrete using a standard truncated cone (see, for example, ASTM C143-15a); however this may also include "slump flow", so the workability is determined using measurement of horizontal concrete spread when released from the cone (see, for example, ASTM C1611-14). slump" may also be used to refer to either or both of these rheological properties and to emphasize that the present invention is not necessarily limited to measurements or monitoring of slump or slump flow, but may comprise related rheology values such as elastic limit, too The term “slump” is used for convenience in this document to refer to concrete rheology and concrete management/monitoring systems.

B. CONCRETE MONITORING SYSTEMS (REDUCTION)

[044] The "energy" (E) associated with the rotation of concrete inside the mixing drum can be monitored using hydraulic pressure sensors, whose output can be correlated to slump, slump flow, elastic limit, viscosity or other value of rheology (see, for example, U.S. Patent No. 8,118,473 to Compton et al., U.S. Patent No. 8,020,431 to Cooley et al., and U.S. Patent No. 8,989,905 to Sostaric et al., to owned by Verifi LLC, a business unit of GCP Applied Technologies Inc. of Cambridge, Massachusetts, USA.

[045] U.S. Patent No. 8,727,604 to Compton et al. (also owned by Verifi, LLC) revealed that sensors for monitoring the hydraulic pressure associated with mixing drum rotation could be used with rotational speed sensors to qualify a current slump calculation based on the hydraulic pressure required to rotate the drum. mixer, so that an accurate history of slump behavior at various drum speeds can be recorded in memory accessible by a computer processor and used later. Preferably, such sensors are used on both the loading and unloading ports of the hydraulic system which controls the mixing drum motor.

[046] The energy associated with the rotation of concrete in a mixing drum can also be monitored using force or tension probes inside the concrete mixing drum. In these cases, the force or tension of the concrete in the probe is measured as the probe rotates through the concrete during drum rotation and is correlated with the slump of the concrete (see, for example, U.S. Patents 8,858,061 and 9,199 .391).

[047] Therefore, hydraulic pressure sensors, force, strain or strain gauges, and the like, can be used in combination with rotational speed sensors (for example, accelerometers as mentioned in U.S. patent No. 8,727,604 to Compton et al.; U.S. Patent Publication No. 2015/0142362 to Jordan et al.; U.S. Patent No. 9,199,391 to Beaupre et al., and U.S. Patent Publication No. 2015/0355160 to Berman, etc.) to provide values output that can be correlated with slump, slump flow, elastic limit, viscosity and/or other rheology values to monitor or predict the behavior or rheological state of a concrete mix in a rotary mixing drum.

[048] Automated concrete slump management (monitoring) systems to manage slump or other rheological properties are commercially available, for example, from Verifi LLC, 62 Whittemore Avenue, Cambridge, Massachusetts, USA, which revealed several methods and systems automated concrete monitoring systems in patent literature, such as U.S. Patents 8,020,431; 8,118,473; 8,311,678; 8,491,717; 8,727,604; 8,746,954; 8,764,273; 8,818,561; 8,989,905; 9,466,803; 9,550,312; PCT/US2015/025054 (Publication No. WO 2015/160610 A1); and PCT/US2014/065709 (Publication No. WO2015073825 A1).

[049] Alternatively, the slump monitoring system can be based on the use of a force sensor that is mounted inside the drum, as taught, for example, in US patents 8,848,061 and 9,625,891 by Berman (Sensocrete Inc ., which is owned by GCP Applied Technologies Inc.), U.S. Patent No. 9,199,391 to Denis Beaupre et al. (Command Alkon Inc.) or Publication No. U.S. 2009/0171595 and WO 2007/060272 to Benegas.

[050] Thus, although the energy/velocity/slump ("EVS") relationships in which energy (E), drum speed (V) and slump (S) can be established using any one of a variety of sensor types, the inventors also consider that the relationship between the correlated energy (whether measured as a pressure, force, or strain reading) changes as the concrete mixer drum speed changes, so that the correlations between E , V and S are not linear in nature. Consequently, the present inventors began to describe the EVS relationship in terms of "slump curves", since a two-dimensional plot of the energy (e.g., hydraulic pressure) associated with rotating concrete at different drum speeds (V) appears as a curved or curvilinear shape rather than a straight line with respect to slump (or slump flow, viscosity, etc.).

[051] Furthermore, these EVS energy/velocity/slump ratios vary for different concrete mixes. In PCT Publication No. WO 2017/099711 entitled “Wide Speed Range Concrete Monitoring Calibration”, Tregger and Roberts et al. revealed a method for calibrating automated monitoring systems by examining EVS ratios across different mixing designs, as well as over a wide range of concrete mixer drum rotational speeds. However, the benefits of the teachings in WO 2017/099771 have resulted in a more refined level of rheological data that otherwise could not be obtained using mere sensors to measure a given rheological property, such as slump, as these benefits are not restricted to measuring only the rebate amount alone.

[052] An analysis of the present invention will be improved by explaining evolutionary advances in monitoring systems (slump) of concrete. This begins with a discussion of how the energy required to rotate concrete in a mixing drum was initially correlated with slump to obtain a “slump curve”. This progresses to a discussion of refinements in the conceptualization of slump curves and slump “ladder” testing. These foregoing problems and their resolution gave rise to the surprising and unpredictable discoveries upon which the present invention is based.

C. WIDE SPEED RANGE JUMPS: CONSTRUCTION OF FALLING STAIRS USING CURVE DATA

[053] Originally, it was assumed that there was a simple relationship between the energy associated with the movement of concrete in a mixing drum and the slump of the mixture at a given drum rotational speed. To understand this relationship, the creator of the monitoring system had to perform what was called a “ladder” process or test. The slump ladder process required the breeder to incrementally adjust slump from 2.54 and 22.86 cm (1 and 9 inches) or more through water additions or addition mixing; and measure the slump manually at each increment using the conventional slump cone method (eg ASTM C143-15a or ASTM C1611-14) to allow the sensor data to be correlated with the measured slump values. As the sensor data was analyzed at different drum speeds, the pressure/velocity/slump relationship could be used to predict slump for the entire fleet. This relationship was called a “debate curve”.

[054] As illustrated in Figure 1, the average drum speed and hydraulic pressures are recorded during a ladder test on each of the three “steps” in drum speed (as shown at times 13:55, 14:00 and 14:02 in Figure 1). At approximately 14:07, a sample is removed from the drum, and the pressure changes to “0”. Subsequently, the slump was adjusted as seen by the pressure drop (at 14:10) so that the process of changing the drum speed could be repeated to generate the slump curve data.

[055] However, it was subsequently realized that a large number of ratios were required for the system to be able to accurately monitor all drum rotational speeds throughout blending projects by ready-mix producers and fleet types of blends. delivery truck. It was also noticed that each type of truck and truck manufacturer had unique properties that affected the generation of slump curve data, which factors often caused slump ladder tests to be run three times for a given producer's fleet. of concrete.

[056] Figure 2 shows the results of multiple slump curves derived from multiple ladder tests. As seen in Figure 2, it was observed that a slump of 4 inches at constant drum rotation speed corresponds to a range of hydraulic pressures from 10 to 14 MPa (1,500 to 2,000 pounds per inch (psi)). This means that a reading of 10 MPa (1500 psi) can correspond to a slump of 8.89 to 17.78 cm (3.5 to 7 inches). These possible correlations were unacceptable for purposes of accurate slump measurement; and thus multiple slump curves needed to be generated. It was realized that viscosity was critical to generating slump curve data, and this required the creation of multiple curves for a single concrete producer.

[057] Initial attempts to resolve this complexity included grouping concrete mixes into mix categories or families of similar mixes in a prescriptive manner, ie considering similar cement content, w/c or aggregate packaging. As there was no easy way to measure the viscosity of a given mixture without additional field testing, the assumption was made that mixtures that had similar constituents would have similar viscosity and slump curves.

[058] In other words, the evident need for stair testing meant a long and arduous stair process, requiring expense in terms of concrete purchases and testing time in terms of weeks if not months to manually lay out the stairways. slump using slump cones. Figure 3 illustrates an exploded number of slump curves that were required, at one point, to be generated for a single concrete producer. Adding to this ladder test complexity presented several difficulties. One difficulty was the fact that the prescriptive batching method tends to be inaccurate at higher drum speeds, as the effect of viscosity could be surprisingly different within a group of blending designs. This was particularly true at lower a/c and higher cement mixes, the slump curve behavior can be more pronounced, thus requiring manual slump cone testing for certain mix designs so that the slump system monitoring is accurate. Finally, the concrete producer's slump curve data was never updated; this became an issue as component materials changed (without warning) and affected concrete performance.

[059] The beginning of the turnaround for the present inventors began with the realization that the manual ladder test could be replaced with the use of monitoring calibration techniques that involve "bouncing" velocity data from the truck-mounted mixing drum that were selectively assimilated from previous deliveries. A process and method for calibrating a vehicle-based concrete delivery monitoring system was taught by Tregger & Roberts et al. In PCT/US2015/064257 (published as International Publication No. WO 2017/09711 A1), which is incorporated by reference herein. These inventors found that drum speeds are constantly changing during delivery over a wide range of drum speeds, and that on multiple strokes the speed changes by more than 4 rpm (hence, "jumps") in either direction (in the mixing or discharging mode) and that the pressure or force corresponding to the movement of the drum accompanied these jumps. They also found that this change occurred in less than five seconds and that the actual slump of the concrete remained the same throughout those five seconds. By measuring the pressure and velocity before and after a velocity jump, and assuming that the slump is equal before and after the velocity jump, then the relationship between Slump1 as a function of (Speed1, Pressure1) and Slump2 as a function of ( Speed2, Pressure2), where Slump1 = Slump2, could mean that there is a functional relationship, F(Speed1, Pressure1) = F(Speed2, Pressure2), such that if the slump is known in Slump1 or Slump2, then the ladders of abatement could be overridden using passively collected sensor data. In order to determine any of the rebates, one of two methods has been suggested. Both methods relied on slump and pressure relationships that could be applied to almost any mix design in a concrete producer's catalogue. The first method took advantage of the fact that at low speed (eg below 3 rpm) one or two pressure-slump ratios can be assumed to cover all mixing designs of a concrete producer. The second method involved one or two relationships between slump and the slope and intercept of a plot of drum rotational speed and pressure to cover all mixing designs of a concrete producer.

[060] Figure 4 illustrates a typical concrete delivery from the “perspective” of drum and pressure velocity sensors from which three jump velocity data can be used to establish the slump curves that replace the ladders. manually obtained. In Figure 4, the solid blue line (associated with the left vertical axis) illustrates the measurement of hydraulic pressure, while the dotted orange line (associated with the right vertical axis) illustrates drum velocity, both measured in relation to time (axis horizontal geometric). After loading, the truck drum speed jumps (approximately 20:25) to perform high-speed mixing (16 to 17 rpm). The drum speed then jumps back and forth and after that the truck drives to the job site using drum speeds in transit (2 to 4 rpm). Upon arrival at the site (approximately 20:52), and shortly before unloading, drum speed increases to high agitation speeds (15 to 17 rpm), and subsequently decreases before unloading. This demonstrates how jump speed data points can be collected for high and low speeds/pressures for the same concrete slump.

D. PAIRING GROUPED SLAUGHTER CURVE DATA WITH ASSIGNED RESISTANCE

[061] Although the aforementioned illustrates the process to start building the relationship between pressure, drum speed and slump, this does not necessarily connect to resistance. To begin with, by compiling large sets of slump curve data obtained from thousands of concrete deliveries involving different types of concrete mix and delivery truck, and examining different ranges of constant velocity, the present inventors have found that certain designs Mixtures of different concrete can demonstrate the same slump curve behavior. In other words, the inventors found that the slump curve data for different mix designs (ie, which have different mix codes) coincided or “clustered” around the same data curve shape or lines; slump curve data is grouped based on performance (rheology), not a prescriptive measurement (ie cement content, w/c, etc.). Again, the term "clustering" or "clustering" or another variant thereof as used in this document means and refers to the action of putting together or compiling hash projects (as identified by a hash code) that have the same behavior as concrete movement. Therefore, the word grouping has both a passive and an active meaning. These grouped mix designs can then be classified according to an assigned strength value.

[062] Figure 5 graphically illustrates the hydraulic pressure and slump relationships at a drum speed and, at first, appears to show four distinct curves, while Figure 6 graphically illustrates that the data set, with the use of different colors, corresponds actually to six different concrete mix designs (ie mix designs that have six different codes and possibly different or similar or the same recipes). The lowermost curve is comprised of purple and green marks (x and o); the green line shown through that bottom curve represents the equation generated by that data. This means that the same equation or data curve can be used to predict slump for both blending designs. It also means that the concretes produced from the two mix designs move the same way (ie, performance-based versus prescriptive grouping).

[063] The present inventors have surprisingly found that two or more mixing designs can have the same curve and therefore a "cluster" of slump curve data that essentially looks like a single-curve phenomenon. From matching the two blending designs illustrated in Figure 6, the present inventors have found that a clustering algorithm can be used that takes into account truck type and blending design for clustering blends on a slump curve if it is determined that blend projects move in the same way. The mathematical field of cluster analysis is a large and active field that includes over one hundred published clustering algorithms. Thus, various mathematical methods can be employed to obtain slump curves that are similar to each other. Examples of clustering algorithms are centroid models, such as the k-means algorithm; distribution models, such as the expectation-maximization algorithm; density models, such as the DBSCAN algorithm; neural models, such as the self-organizing map algorithm, and soft clustering models, such as fuzzy clustering models, which determine how objects belong in a cluster and their “degree” of fit. As an example, two sets of slump curve data can be merged if the resulting slump curve determined from each of the data sets predicts the slump values close enough to each other (e.g., the predictions are within 1 cm (1/2 inch) from each other).

[064] The present invention is based on the ability to "group" the slump curve data, that is, when two or more (and preferably a plurality) of concrete mix projects move in a similar way or, in in other words, they have the same energy (eg pressure)/velocity/slump ratio. As shown in Figure 6, the two individual mix designs (that is, which have different mix codes) cluster along the same curve. One can see evidence of numerous instances of grouping in a concrete producer's mix design catalog, where mix designs that have different mix codes have the same rheological fingerprint. For example, a mix design catalog containing 1000 mix codes can be reduced by cluster analysis to 20 characteristic slump data curves. Surprisingly, many projects that do not have the same component or recipe can share the same abatement curve and therefore be found within the same grouping of curve data points (for example, as can be seen visually when the data is displayed in a graphic).

[065] The ability to classify how concrete moves allows the present inventors to align this classification with another characterization, namely, the strength value that was assigned by the concrete producer to the concrete mix design (hereinafter “assigned strength” ). The present inventors believe that this will allow concrete producers to reduce the size of the mix catalogue, to create a preferred mix list, and to improve quality control. If concrete mixes are found to move the same way and have the same strength, there is no reason to have multiple mix projects. The lower the mix count, the greater then can be the volume of slump curve data generated for the particular mix design, and therefore the volume of strength test results (e.g. cylinder test, cube); and this can provide a greater amount of quality control or accuracy in slump curve predictions, for example, than can be produced by the monitoring system processor unit.

[066] Figure 7 is a flow chart showing an exemplary process of the present invention. In block 2, a mixture project catalog (or a portion, for example all residential mixtures) is provided, comprising mixture projects with a mixture code; assigned strengths (eg design strengths as determined using ACI 211.4-91 and ACI 318-14); and slump curve data. The slump curve data can be any data used to predict rheology (ie slump) based on movement detected in the rotating concrete mixing drum. For example, slump curve data may comprise jump speed events that include drum rotational speed and corresponding hydraulic pressure readings before and after the event.

[067] In block 4, the slump curve data is prepared for cluster analysis. For example, with jump speed data, each jump speed event can be plotted on an x-y plot, where drum rotational speed is plotted on the x axis and hydraulic pressure is plotted on the y axis. For each jump speed event, a line can be drawn through the two points (representing the drum rotation speed and pressure before and after the jump speed), and the slope and intercept can be calculated.

[068] Once these values are calculated, they can be plotted in the slope-intercept space, here the intercept is plotted on the x-axis and the slope on the y-axis (or vice versa), as shown in the block 6. With this space being defined and populated using the data, a clustering algorithm can be used to determine groupings within the space. The clustering algorithm can be based on any one of several different clustering methods. For example, an unsupervised machine learning algorithm can be used, such as a k-means algorithm (see, for example, Hartigan, J. A.; Wong, M. A. (1979). “Algorithm AS 136: A K-Means Clustering Algorithm Journal of the Royal Statistical Society. Series C (Applied Statistics). 28(1): 100-108). After the clusters are formed, slump curve relationships can be created for each cluster, and subsequently the prediction accuracy of each slump curve relationship can be determined. If the accuracy is not sufficient (above a predefined accuracy, for example 90% of the prediction is 1.27 cm (0.5 inch) from the actual slump), the cluster analysis can be refined, for example to have more clusters finely divided).

[069] Alternatively, jump speed events can be plotted in an x-y-z plot where, for example, drum rotational speed is plotted on the x axis, hydraulic pressure is plotted on the y axis, and slump is plotted on the y axis. z axis. Cluster analysis can then be performed on this "EVS" space to determine clusters of slump curve data.

[070] In block 8, once the slump curve clusters have been sufficiently discerned or identified, an identification code or name tag may be assigned to the cluster to facilitate subsequent clustering.

[071] In block 10, the assigned resistances are grouped into predefined classes, for example, resistances between 20.68 and 27.58 MPa (3,001 and 4,000 psi) are placed in a class; strengths between 27.59 and 34.47 MPa (4001 and 5000 psi) are placed in another class. More preferably, smaller subdivisions can be used, and from a practical perspective, classes are assigned by range minimum, not average. This gives a conservative perspective to the data.

[072] In block 12, a mixture design can be chosen within the same abatement curve grouping ID and assigned resistance class, based on a cost, performance or other characteristic, for example, lower cost. This process can be achieved in several different ways. First, with the use of a fixed selection characteristic (or group of selection characteristics), all mixture design groups with the same grouping of slump curves and strength class can be reduced to the minimum number of design designs. blends that still include the given selection characteristic. For example, within the same grouping of slump curves and strength class, only the lowest cost mix may be retained for batch selection when a mix design that requires the given rheology of grouping curves and strength class is necessary. As another example, mixes with the highest volume of deliveries can be kept for either an entrained version or a non-entrained version. Mixing designs that are not retained in these two examples can be, for example, excluded from further consideration, archived, or deleted from the mixing design catalogue. Alternatively, the associated data (slump curve data, strength data or other data) can be merged with the retained mix design (or designs). Regardless of the fate of the unretained mix designs, the retained mix designs, with their future use will accumulate quality control data for better control.

[073] In block 14, the selected mixing project is grouped into batches.

[074] Figure 8 is a two-dimensional histogram in which 608 concrete mixing projects (ie 608 different codes) were monitored. Nine different slump curves were discerned between these mix designs for various assigned strength values in the range of 27.58 to 82.74 MPa (4,000 to 12,000 psi). The highest peak, which indicates over 100 different mix designs (codes) can be readily seen for slump curve #1 at the assigned strength of 48.26 MPa (7,000 psi), and this visually represents a slump curve very dense data.

[075] Figure 9 is a two-dimensional representation of the histogram of Figure 7, which indicates that 608 concrete mix designs actually represent only 37 groups of slump curve - strength.

[076] As an additional advantage of the present invention, new mixtures can be adjusted to a given application with much higher confidence. Typically, laboratory tests are performed to validate the design. However, this method may not represent actual performance, as in a small laboratory mixer, it does not represent actual mixing experienced in a mixer truck. However, by interpolating between existing mix designs with their associated data (ie strength and rheology), mix designs with accurate strength and rheology characteristics (in addition to a simple slump value) can be developed. moreover, the amount of associated data gets realistic validation compared to lab tests. Such data can be extremely useful as supporting data for submissions for a given job.

[077] In a first exemplary embodiment, the present invention provides a process for managing a plurality of mixing designs in the mixing design catalog of a concrete producer, comprising: collecting slump curve data obtained during the monitoring of loads of individual concrete produced from a plurality of mix designs, where each mix design is identified by a different identification code irrespective of whether the mix components are different or identical; grouping slump curve data having the same motion characteristics into at least two slump curve data groupings; associate each mix design within the slump curve data cluster with an assigned strength value; and selecting a mix design to produce, to display, or both to produce and to display, from among the two or more individual mix designs within the same slump curve data cluster, the selection being based on the same value of assigned strength and at least one selection factor chosen from among cost, performance, physical appearance, quality or combination thereof.

[078] In a second exemplary embodiment, which may be based on the first exemplary embodiment, the invention provides a process in which, when selecting the mixture design, the at least one selection factor is chosen from (a) material cost of the mixing design; (b) material cost of any of the blending components; (c) number of past deliveries; (d) total volume delivered from a particular concrete mix project; (e) number of available stress test results; (f) shipment approval statuses; (g) source of materials used in the concrete mix; (h) a characteristic or property of an aggregate material used in the mix design (eg mineralogical nature of the aggregate, aggregate shape or size such as maximum particle size, pitch fraction, etc.); (i) a cement hydration characteristic or property used in the mix design (eg w/c, initial setting time, final setting time, etc.); (j) a packing density characteristic or property within the concrete mix; (k) a characteristic or property of the durability or reactive nature of the concrete mix (eg chloride permeability, susceptibility to alkali-silica reaction); (I) a characteristic or property of placing the concrete mix; (m) chemical addition mix used in concrete mixing (eg type of addition mix, nature of high range water reducing effect, accelerators, retarders, effect of combinations of addition mixes, etc.); (n) air characteristic of concrete (eg air content factor, air distribution, air spacing, etc.); (o) diameter of hose or pipe used to transport concrete from the delivery truck, mixer or pump to the placement site at the construction site; or (p) a combination of any of the aforementioned factors.

[079] In a third exemplary embodiment, which is as described above in relation to any of the first and second exemplary embodiments above, the invention provides a process in which the grouping comprises sets of slump curve data associated with different projects of blending, such that the slump predictions from the slump prediction ratios derived from each individual slump curve data are within a predefined tolerance (e.g. +/- 1 cm (0.5 inch) slump ).

[080] In a fourth exemplary embodiment, which is as described above in relation to any of the first and third exemplary embodiments above, the invention provides a process in which, when collecting slump curve data obtained during the monitoring of loads concrete mixes produced from a plurality of mix designs, the slump curve data is derived from jump velocity data, where slump, drum rotational speed, and force associated with the rotation of the concrete mix in a drum rotary mixer are obtained before and after jumps in drum speed, where the jump in drum speed is at least three (and more preferably at least four) drum revolutions per minute difference. These factors (eg slump, drum rotation speed and force associated with rotating the concrete mix in a rotating mixing drum) can be saved in a computer accessible database as grouped relationships. They can be graphically represented (and as such are described herein in terms of “slump curve data”) and displayed in any number of ways. Slump curve data can be defined in terms of force (e.g. hydraulic pressure sensor readings) versus drum speed (e.g. revolutions per minute at a first drum speed and at a second drum speed which was suddenly changed by at least 3 or 4 RPM compared to the first drum speed). Data comprising y-intercepts (that is, the pressure value when the velocity is extrapolated to zero) and slope (of the pressure values at the two drum velocity values) can be subjected to cluster analysis to discern mixtures that have common rheological behavior (as might be suggested by a cloud of points plotted on a graph suggesting a singular common trend or singular common clustering - or, in other words, where the points appear to coincide).

[081] In a fifth exemplary embodiment, which is as described above in relation to any of the first to fourth exemplary embodiments above, the invention provides a process in which, when collecting slump curve data obtained during the monitoring of loads of individual concrete mixes produced from a plurality of mixing designs, slump data curves are established using sensors to measure the force associated with rotating concrete mixes in a rotating mixing drum, said force sensors are chosen from the hydraulic pressure sensor, strain or strain measuring device located inside the rotating mixing drum, or both.

[082] In a sixth exemplary embodiment, which is as described above in relation to any of the first to fifth exemplary embodiments above, the invention provides a process in which, when collecting slump curve data obtained during the monitoring of loads of individual concrete produced from a plurality of mixing designs, the slump data curves are established using hydraulic pressure sensors comprising a first sensor for measuring hydraulic pressure when the mixing drum is rotating in the loading direction, and a second sensor to measure hydraulic pressure when the mixing drum is rotating in the discharge direction.

[083] In a seventh exemplary embodiment, which is as described above in relation to any of the first to sixth exemplary embodiments above, the invention provides a process in which, when collecting slump curve data obtained during the monitoring of loads of individual concretes produced from a plurality of mixing designs, the slump data curves are established using a strain or stress measuring device located within the mixing drum.

[084] In an eighth exemplary embodiment, which is as described above in relation to any of the first to seventh exemplary embodiments above, the invention provides a process in which, when collecting abatement curve data obtained during delivery monitoring in In transit of individual concrete loads produced from a plurality of mixing designs, the slump data curves are established using a drum velocity sensor comprising an accelerometer, a gyroscope or combination thereof.

[085] In a ninth exemplary embodiment, which is as described above with respect to any of the first to eighth exemplary embodiments above, the invention provides a process in which, in the step of grouping curve data that have the same characteristics as movement according to the assigned strength value, at least two (more preferably at least three, and most preferably at least ten) different mix designs (which are identified as different by having different codes but having the same mix components ) are used to produce concrete mix loads from which slump curve data is obtained to define the same slump curve and therefore define a grouping of slump curve data.

[086] In a tenth exemplary embodiment, which is as described above in relation to any of the first to ninth exemplary embodiments above, the invention provides a process in which the assigned strength values are based on physical strength, modulus of elasticity, water content, cement content, maturity test or combination thereof.

[087] In an eleventh exemplary embodiment, which is as described above in relation to any of the first to tenth exemplary embodiments above, the invention provides a process in which, when collecting abatement curve data obtained during delivery monitoring in transit of individual concrete loads produced from a plurality of mixing designs, the slump curve data establishes at least three (and more preferably at least five) different slump curve data groupings; and are correlated with at least three (and more preferably at least five) assigned strength values.

[088] In a twelfth exemplary embodiment, which is as described above in relation to any of the first to eleventh exemplary embodiments above, the invention provides a process in which a concrete mixing design is selected from a pool of data slump curve to an assigned strength (eg value or number) by computer processor operation, and a concrete mix is generated. In a further example of this particular aspect, the computer processor was programmed to select the concrete mix design and to instruct that a concrete mix be produced (e.g. by sending a signal to the batch processing computer at the plant batch processing) according to the selected mixing design. Preferably, the computer processor is programmed to initiate this function without additional input from a human operator or manager.

[089] In a thirteenth exemplary embodiment, which is as described above with respect to any one of the first to twelfth exemplary embodiments above, the invention provides a method in which a histogram (see, for example, Figure 8) or graph (see, for example, Figure 9) is generated to graph, on a monitor screen or other visual display, the slump curve data groupings for each assigned strength value.

[090] In a fourteenth exemplary embodiment, which is as described above with respect to any one of the first to thirteenth exemplary embodiments above, the invention provides a method in which the histogram or graph displayed on a monitor screen is a GUI (graphical user interface) that allows a user to click through to see a list of mix codes for a given grouping of slump curve data.

[091] In a fifteenth exemplary embodiment, which is as described above in relation to any one of the first to fourteenth exemplary embodiments above, the invention provides a process in which, after selecting a mixing design to produce, to display, or for both output and display, out of the two or more individual blend designs within the same slump curve data cluster, at least one blend design is removed from the same slump curve data cluster. For example, one or more of the selection factors identified in the second exemplary aspect discussed above can be used to inactivate or remove from the producer's catalog those mix designs that exceed a given cost threshold, employ a given cement or aggregate material, or that meet other selection criteria based on the selection factors.

[092] In a sixteenth exemplary embodiment, the invention provides a system for managing a plurality of mixing projects in the mixing project catalog of a concrete producer comprising: a plurality of ready-mix concrete delivery trucks, each one having a computer processing unit (CPU) communicative with a first sensor or sensors for measuring the energy associated with the rotation of a batch of concrete mix within a rotating mixing drum (e.g., such as hydraulic pressure sensors, sensors of the strain or strain gauge type, etc.) and communicative with a second sensor to measure the speed of rotation of the mixing drum (for example, an accelerometer), in which the CPUs are programmed to store in the memory accessible by the CPU, a plurality of slump curve data obtained during transit delivery monitoring of individual concrete batches produced from a plurality of mix designs (as identified by mix design number or individual identification code, regardless of whether their components mixture are identical or different); and a computer processing unit that is programmed (the computer processor is a chip, circuit, machine, hardware, etc., in the truck, remote location, for example, so-called cloud-based system that is not necessarily in the truck or control center location): (a) gather (e.g. collate) the slump curve data that has been obtained during and from in-transit delivery monitoring of individual concrete loads produced from a plurality of construction projects mix (as identified by mix design number or individual identification code, regardless of whether your mix components are identical or different) according to assigned strength values; and (b) selecting, displaying, or both selecting and displaying a preferred mix design chosen from a pool of a plurality of slump curve data at a given assigned strength value, based on at least one selection factor (for (e.g. mix or total mix component costs, cement type, aggregate type, addition mix type, w/c and many other possible selection factors).

[093] In a seventeenth exemplary embodiment, which is described above in relation to the sixteenth exemplary embodiment described above, the invention provides a system in which, when selecting the mixing design, the at least one selection factor is chosen from ( a) material cost of the mixing design; (b) material cost of any of the blending components; (c) number of past deliveries; (d) total volume delivered from a particular concrete mix project; (e) number of available stress test results; (f) shipment approval statuses; (g) source of materials used in the concrete mix; (h) a characteristic or property of an aggregate material used in the mix design (eg mineralogical nature of the aggregate, aggregate shape or size such as maximum particle size, pitch fraction, etc.); (i) a cement hydration characteristic or property used in the mix design (eg w/c, initial setting time, final setting time, etc.); (j) a packing density characteristic or property within the concrete mix; (k) a characteristic or property of the durability or reactive nature of the concrete mix (eg chloride permeability, susceptibility to alkali-silica reaction); (I) a characteristic or property of placing the concrete mix; (m) chemical addition mix used in concrete mixing (eg type of addition mix, nature of high range water reducing effect, accelerators, retarders, effect of combinations of addition mixes, etc.); (n) air characteristic of concrete (eg air content factor, air distribution, air spacing, etc.); (o) diameter of hose or pipe used to transport concrete from the delivery truck, mixer or pump to the placement site at the construction site; or (p) a combination of any of the aforementioned factors.

[094] In an eighteenth exemplary embodiment, a process for creating a new concrete mixing design comprising: collecting slump curve data obtained while monitoring individual concrete loads produced from a plurality of concrete mixing designs concrete, where each concrete mix design corresponds to a different identification code regardless of whether the mix components are different or identical; grouping slump curve data having the same motion characteristics into at least two slump curve data groupings; associate each mix design within the slump curve data cluster with an assigned strength value; enter a target strength and rheology; interpolate mix design components based on at least two existing mix designs where strength and rheology targets are satisfied; and creating a new mix project to produce, display, or both produce and display, based on mix design components interpolated from the at least two existing mix designs. This eighteenth exemplary embodiment may be based on or incorporate any of the features described above with respect to the first through seventeenth exemplary embodiments.

[095] Although the invention is described herein using a limited number of embodiments, these specific embodiments are not intended to limit the scope of the invention as described and otherwise claimed herein. There are modifications and variations of the described modalities. More specifically, the examples below are given as a specific illustration of embodiments of the claimed invention. It should be understood that the invention is not limited to the specific details set forth in the examples. All parts and percentages in the examples, as well as the remainder of the specification, are in percent dry weight unless otherwise specified.

EXAMPLE 1

[096] As an example of the surprising advantages and benefits of the present invention, the present inventors considered the mixing design catalog of an actual concrete producer which contained 608 mixing designs (as identified by 608 different mixing codes). Indeed, this was a subset of the entire mixture catalog because it was limited to a given region, which used the same aggregate source. Mix designs have been filtered to only include coarse aggregates that have a nominal size of 2.54 cm (one inch). This filtering process can alternatively take place after applying the inventive steps of Figure 7, by choosing at least one blend to represent a given strength and rheology characteristic. When organized by strength and rheology (slump ratio), the histogram in Figure 8 shows the numerous mix designs with the same properties. After applying the inventive steps in Figure 7, the histogram indicates that the mix designs in the “buckets” or strength and rheology clusters shown in Figure 9 make up 37 in total, and this represents a 96% reduction in terms of the previous total number. of mix designs in collection.

EXAMPLE 2

[097] As a second example, the same reduced set of mix designs in the first example can be used to determine a new mix design with a given set of criteria, such as a strength class and a rheology class.

[098] As illustrated in a hypothetical example that is illustrated using the two-dimensional graph in Figure 10 (which is based on Figure 8 discussed above), a concrete producer may wish to provide a mixing design with a slump and strength curve design in the space indicated by the bucket or square designated "x" in Figure 10. Due to the fact that no mix design currently exists (for certain combinations of strength classes and rheology), the producer will need to design a new mix.

[099] To design a new mixture (for bucket "x"), the producer can use the production data corresponding to adjacent buckets, such as using interpolated values based on adjacent buckets. For example, an interpolation can be performed by averaging mix ratios belonging to buckets 1a and lb. Consequently, a new mixture for "x" can be designed.

[0100] Additional exemplary methods of the invention may include averaging other adjacent mixing designs, such as averaging bucket values from buckets, for example, 2a + 2b; 3a+3b; 4a + 4b, or combinations thereof. The interpolated values for a given "x" bucket may involve values from adjacent spaces in the existing mix design catalog, such as from buckets that may be horizontally, vertically or diagonally adjacent (in the two-dimensional graphical representation provided in Figure 10).

[0101] A key advantage of this exemplary method is that actual production data is used to create the new mix design, as opposed to lab tests which may not reflect what will actually be produced.

[0102] Thus, the invention provides an exemplary process for creating a new concrete mixing design comprising: collecting slump curve data obtained during monitoring of individual concrete loads produced from a plurality of concrete mixing designs concrete, where each concrete mix design corresponds to a different identification code regardless of whether the mix components are different or identical; grouping slump curve data having the same motion characteristics into at least two slump curve data groupings; associate each mix design within the slump curve data cluster with an assigned strength value; enter a target strength and rheology; interpolate mix design components based on at least two existing mix designs where strength and rheology targets are satisfied; and creating a new mix project to produce, display, or both produce and display, based on mix design components interpolated from the at least two existing mix designs.

[0103] The present invention is described herein using a limited number of illustrative embodiments not intended to limit the scope of the invention.

Claims (18)

1. Process for managing a plurality of mix designs in a concrete producer mix design catalog CHARACTERIZED in that it comprises: collecting slump curve data obtained during monitoring of individual concrete loads produced from a plurality mixed mixing designs, where each mixing design is identified by a different identification code regardless of whether the mixing components are different or identical; wherein by collecting slump curve data obtained during monitoring of individual concrete loads produced from a plurality of varying mix designs, slump data curves are established using sensors to measure force associated with rotating concrete mixes in a drum rotary mixer, said force sensors being chosen from a hydraulic pressure sensor, strain or tension measuring device located in the rotary mixing drum, or both; grouping slump curve data having the same motion characteristics into at least two slump curve data groupings; associate each mix design within the slump curve data cluster with an assigned strength value; select a mix design to produce, to display, or both to produce and to display, from among two or more individual mix designs within the same cluster of slump curve data, where the selection is based on the same strength value assigned and at least one selection factor chosen from among cost, performance, physical appearance, quality or combination thereof; and concentrating performance information in said mix design catalog by merging slump curve data, strength data or other data associated with the unselected mix designs with the selected mix design. 2. Process, according to claim 1, CHARACTERIZED by the fact that when selecting the mixture design, at least one selection factor is chosen from (a) material cost of the mixture design; (b) material cost of any of the blending components; (c) number of past deliveries; (d) total volume delivered from a particular concrete mix project; (e) number of available stress test results; (f) shipment approval statuses; (g) source of materials used in the concrete mix; (h) a characteristic or property of an aggregate material used in the blending project; (i) a hydration characteristic or property of the cement used in the mix design; (j) a packing density characteristic or property within the concrete mix; (k) a characteristic or property of the durability or reactive nature of the concrete mix; (I) a characteristic or property of placing the concrete mix; (m) a chemical addition mixture used in mixing concrete; (n) an air characteristic of the concrete; (o) a diameter of hose or pipe used to transport concrete from a delivery truck, mixer or pump to the actual placement site at the construction site; or (p) a combination of any of the aforementioned selection factors. 3. Process, according to claim 1, CHARACTERIZED by the fact that the grouping comprises sets of slump curve data associated with different mixing designs, so that slump predictions of slump prediction ratios derived from each data from individual slump curve are within a predefined tolerance. 4. Process, according to claim 1, CHARACTERIZED by the fact that, when collecting slump curve data obtained during monitoring of individual concrete loads produced from a plurality of varied mixing designs, the slump curve data are derived from jump speed data where slump, drum rotation speed and force associated with the rotation of the concrete mix in a rotary mixing drum are obtained before and after jumps in drum speed, where the jump in drum speed is at least three drum revolutions per minute difference. 5. Process, according to claim 1, CHARACTERIZED by the fact that, when collecting slump curve data obtained during monitoring of individual concrete loads produced from a plurality of varied mixing designs, the slump data curves are established using sensors to measure force associated with rotating concrete mixes in a rotating mixing drum, said force sensors being chosen from a hydraulic pressure sensor, strain or strain measuring device situated within the rotating mixing drum, or both. 6. Process, according to claim 1, CHARACTERIZED by the fact that, when collecting slump curve data obtained during monitoring of individual concrete loads produced from a plurality of varied mixing designs, the slump data curves are established using hydraulic pressure sensors comprising a first sensor for measuring hydraulic pressure when the mixing drum is rotating in the loading direction, and a second sensor for measuring hydraulic pressure when the mixing drum is rotating in the discharging direction. 7. Process, according to claim 1, CHARACTERIZED by the fact that, when collecting slump curve data obtained during monitoring of individual concrete loads produced from a plurality of varied mixing designs, the slump data curves are established using a strain or strain measuring device located within the rotating mixing drum. 8. Process, according to claim 1, CHARACTERIZED by the fact that, when collecting slump curve data obtained during in-transit delivery monitoring of individual concrete loads produced from a plurality of varied mixing designs, the curves of slump data are established using a drum speed sensor comprising an accelerometer, a gyroscope or combination thereof. 9. Process, according to claim 1, CHARACTERIZED by the fact that, in the step of grouping slump curve data that have the same movement characteristics according to the assigned resistance value, at least two different mixing designs are used to produce concrete mix loads from which slump curve data are obtained to define a single slump curve and therefore define a grouping of slump curve data. 10. Process, according to claim 1, CHARACTERIZED by the fact that the assigned strength values are based on physical strength, modulus of elasticity, water content, cement content, maturity test or combination thereof. 11. Process, according to claim 1, CHARACTERIZED by the fact that, when collecting slump curve data obtained during monitoring of delivery in transit of individual concrete loads produced from a plurality of varied mixing designs, the data slump curve data set at least three different slump curve data groupings; and are correlated with at least three assigned resistance values. 12. Process, according to claim 1, CHARACTERIZED by the fact that a concrete mix design is selected from a pool of slump curve data for a strength assigned by computer processor operation, and a concrete mix is generated. 13. Process, according to claim 1, CHARACTERIZED by the fact that a histogram or graph is generated to graphically represent, on a monitor screen or other visual display, groupings of slump curve data for each assigned resistance value. 14. Process according to claim 13, CHARACTERIZED by the fact that the histogram or graph displayed on a monitor screen is a GUI (graphical user interface) that allows a user to click to see a list of mixing codes for a given cluster of slump curve data. 15. Process, according to claim 1, CHARACTERIZED by the fact that, after selecting a mixing project to produce, to display, or both to produce and to display, among the two or more individual mixing projects within the same grouping of slump curve data, at least one blend design is removed from the same slump curve data cluster. 16. System of the invention for managing a plurality of mixing projects in a mixing project catalog of a concrete producer, CHARACTERIZED by the fact that it comprises: a plurality of ready-mix concrete delivery trucks, each having a unit of computer processing (CPU) communicative with a first sensor or sensors for measuring the energy associated with the rotation of a batch of concrete mix within a rotating mixing drum and communicative with a second sensor for measuring the speed of rotation of the mixing drum, in that the CPUs are programmed to store in CPU-accessible memory a plurality of slump curve data obtained during in-transit delivery monitoring of individual concrete batches produced from a plurality of varied mixing designs; and a computer processing unit that is programmed (a) to gather slump curve data that has been obtained during and from in-transit delivery monitoring of individual batches of concrete produced from a plurality of varied mixing designs according to assigned resistance values; and (b) to select, to display, or both to select and to display a preferred mix design chosen from a pool of a plurality of slump curve data at a given assigned strength value, based on at least one factor of selection; and (c) merge performance information into said mix design catalog by merging slump curve data, strength data or other data associated with the unselected or displayed mix designs with the selected and/or displayed mix design. 17. System, according to claim 16, CHARACTERIZED by the fact that, when selecting the mixing design, at least one selection factor is chosen from (a) material cost of the mixing design; (b) material cost of any of the blending components; (c) number of past deliveries; (d) total volume delivered from a particular concrete mix project; (e) number of available stress test results; (f) shipment approval statuses; (g) source of materials used in the concrete mix; (h) a characteristic or property of an aggregate material used in the blending project; (i) a hydration characteristic or property of cement used in the mix design; (j) a packing density characteristic or property within the concrete mix; (k) a characteristic or property of the durability or reactive nature of the concrete mix; (I) a characteristic or property of placing the concrete mix; (m) a chemical addition mixture used in mixing concrete; (n) an air characteristic of the concrete; (o) a diameter of hose or pipe used to transport concrete from a delivery truck, mixer or pump to the actual placement site at the construction site; or (p) a combination of any of the aforementioned selection factors. 18. Process for creating a new concrete mix design CHARACTERIZED in that it comprises: collecting slump curve data obtained during monitoring of individual concrete loads produced from a plurality of varied concrete mix designs, where each concrete mix project corresponds to a different identification code regardless of whether the mix components are different or identical; wherein by collecting slump curve data obtained during monitoring of individual concrete loads produced from a plurality of varying mix designs, slump data curves are established using sensors to measure force associated with rotating concrete mixes in a drum rotary mixer, said force sensors being chosen from a hydraulic pressure sensor, strain or tension measuring device located in the rotary mixing drum, or both; grouping slump curve data having the same motion characteristics into at least two slump curve data groupings; associate each mix design within the slump curve data cluster with an assigned strength value; input a resistance and rheology targets into a computer processor; interpolate mix design components based on at least two existing mix designs where strength and rheology targets are satisfied; and creating a new mix project to produce, to display, or both to produce and to display, based on the mix design components interpolated from the at least two existing mix designs; and concentrating performance information in said mix design catalog by merging slump curve data, strength data or other data associated with the unselected mix designs with the selected mix design.