CN106528990A - Hypersonic velocity pointed conical appearance heat flux density modeling approach based on functional optimization - Google Patents
Hypersonic velocity pointed conical appearance heat flux density modeling approach based on functional optimization Download PDFInfo
- Publication number
- CN106528990A CN106528990A CN201610955734.4A CN201610955734A CN106528990A CN 106528990 A CN106528990 A CN 106528990A CN 201610955734 A CN201610955734 A CN 201610955734A CN 106528990 A CN106528990 A CN 106528990A
- Authority
- CN
- China
- Prior art keywords
- tunnel
- wind
- hypersonic
- heat flux
- functional
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/30—Circuit design
- G06F30/36—Circuit design at the analogue level
- G06F30/367—Design verification, e.g. using simulation, simulation program with integrated circuit emphasis [SPICE], direct methods or relaxation methods
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
Landscapes
- Engineering & Computer Science (AREA)
- Computer Hardware Design (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Microelectronics & Electronic Packaging (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Aerodynamic Tests, Hydrodynamic Tests, Wind Tunnels, And Water Tanks (AREA)
Abstract
The invention relates to a hypersonic velocity pointed conical appearance heat flux density modeling approach based on functional optimization. The approach comprises the steps of utilizing a hypersonic velocity calorimetric wind tunnel to conduct a ground calorimetric test on n pointed conical models with different shrink ratios of an aircraft; obtaining heat flux density distribution laws of n models with different shrink ratios in the hypersonic velocity calorimetric wind tunnel to obtain heat flux density test values Qwi respectively, wherein 1<=i<=n; adjusting wind tunnel test parameters in the hypersonic velocity calorimetric wind tunnel, and obtaining a first set of heat flux density test values Qwij, wherein j is wind tunnel test times; obtaining heat flux density distribution laws of a first set of aircrafts; totally obtaining heat flux density distribution laws Qwk of k sets of aircrafts; applying a functional optimization algorithm, introducing a wind tunnel quality variable a and a calibration model parameter b, conducting iterative operation on Qwk, solving an optimal spatial alternation, and obtaining pointed conical heat flux density model Qw. The hypersonic velocity pointed conical appearance heat flux density modeling approach based on the functional optimization avoids one-sidedness of a modeling method in the prior art and interference of human experience factors.
Description
Technical field
The present invention relates to a kind of hypersonic pointed cone profile heat flow density modeling method optimized based on functional, belongs to modeling
Field.
Background technology
High-altitude, it is hypersonic under the conditions of, aircraft surface can produce the Aerodynamic Heating with very strong destructive power, its heat flow density
Affected by flight Mach number, local Reynolds number, the vibrational excitation of gas molecule, the dissociation even many factors such as ionization, predicted
Modeling is difficult.Pointed cone has basis for the design of whole aircraft as a kind of representative configuration, its heat flow density of accurate description
Guiding significance.
At present, for hypersonic heat flow density, both at home and abroad all in engineering approximation theoretical method, fluid calculation numerical simulation
Three aspects such as method, ground/flight test procedure are studied.The U.S. was have developed a series of from the seventies in last century
Aerodynamic Heating engineering approximation method software (AEROHEAT, LATCH, MINVER, UNLATCH2, UNLATCH3 etc.) and fluid calculation number
Value analogy method software (DPLR, FUN3D, GASP, LAURA, US3D etc.) (reference：Hypersonic and high-temperature aerodynamics (the
2 editions), Anderson, aerospace industry publishing house, in September, 2003)；And carry out large number of ground test with flying demonstration checking examination
Test, have been built up the more ripe predicting means of flight mission profile aerodynamic force thermal environment.Europe, Japanese (JAXA) etc. are also all
Possess certain hypersonic heat flow density to calculate and test capability.Domestic Aerospace Science and Technology Corporation, Chinese Academy of Sciences's mechanics study
Institute, the Chinese research unit such as aerodynamic investigation and centre of development, China Aerospace aerodynamic investigation institute, the National University of Defense technology are all
Develop the hypersonic heat flow density of oneself and calculated software, possess hypersonic hot-fluid test capability and the test of continuous improvement
Technology (reference《Chinese scientific strategy hydrodynamics》, Science Press, in September, 2014).
Make a general survey of both at home and abroad, although reliable heat flow density data can be obtained under local condition, due to different wind-tunnel
It is different to the simulation context of flow parameter, thus heat flow density reflects different physical mechanisms, heat flux distribution rule disunity,
The modeling of aircraft thermal environment mainly according to certain experience and it is assumed that provide engineering approximation and fitting, still lack objectively, have
There is the theoretical method of certain universality.
How to provide a kind of accurate response hypersonic pointed cone profile heat flux distribution Mathematical Modeling, be this area urgently
The technical problem of solution.
The content of the invention
It is an object of the invention to overcome the deficiencies in the prior art, there is provided a kind of hypersonic pointed cone optimized based on functional
Profile heat flow density modeling method, it is to avoid the one-sidedness of modeling method, reduces the interference of artificial sense datum.
The object of the invention is achieved by following technical solution：
A kind of hypersonic pointed cone profile heat flow density modeling method optimized based on functional is provided, is comprised the steps：
(1) using hypersonic calorimetric wind-tunnel, ground calorimetric examination is carried out to the pointed cone model of n different contracting ratios of aircraft
Test；
(2) obtain heat flux distribution rule of the n different scale models in hypersonic calorimetric wind-tunnel respectively to obtain
Heat flow density test value Qwi, wherein 1≤i≤n；
(3) the wind tunnel test parameter of hypersonic calorimetric wind-tunnel is adjusted, first group of heat flow density test value Qwij, j is obtained
For wind tunnel test number of times；
(4) obtain heat flux distribution rule Qw1=fij of first group of aircraft1(T0,P0,H0,Hw,p,ρ,u,M,
ReL, Rex), wherein T0 be wind-tunnel stagnation temperature, P0 be wind-tunnel stagnation pressure, H0 be wind-tunnel total enthalpy, Hw be wind-tunnel wall enthalpy, p is flowing pressure
Power, ρ be come current density, u for velocity vector, M be Mach number, ReL be unit Reynolds number, Rex be local Reynolds number；
(5) k-1 different hypersonic calorimetric wind-tunnel is changed, repeat step (1)-(4) obtain k group aircraft altogether
Heat flux distribution rule Qwk=fijk(T0,P0,H0,Hw,p,ρ,u,M,ReL,Rex)；
(6) using functional optimized algorithm, wind-tunnel qualitative variables a and mark mould parameter b is introduced, calculating is iterated to Qwk, is asked
The spatial alternation of optimum is taken, the expression formula of pointed cone heat flow density model Qw=f (t) is obtained.
Preferably, also including step (7), carry out calculating the calculating data of acquisition according to Qw=f (t), try with practical flight
Data Comparison is tested, when required precision is met, Qw function expressions is determined；When precision is unsatisfactory for required precision, return to step
(6), regain the function expression of Qw.
Preferably, k different hypersonic calorimetric wind-tunnel includes shock tunnel and gun wind tunnel.
Preferably, functional optimized algorithm is applied in step (6), introduces wind-tunnel qualitative variables a and mark mould parameter b, Qwk is entered
Row iteration is calculated, and the concrete grammar for obtaining pointed cone heat flow density calculating model Qw is：Calculated using functional optimization in function space
Method seeks f (t) the function representation forms with least complex.
Preferably, f (t) the function representation shapes with least complex are sought using functional optimized algorithm in function space
The concrete grammar of formula is：Using heat flux distribution rule Qwk=fij of k group aircraftk(T0,P0,H0,Hw,p,ρ,u,M,
ReL, Rex), substitute into formulaMost adaptation function shape is searched in canonical function storehouse
Formula g (t)；
F (t) is default solved function form；G (t) is canonical function form；It is empty in Hilbert for f (t), g (t)
Between angle；
G (t) and Qw has following relation：
C+d/ (v+Rex)-Qw/ (ρ * u) (H0-Hw)=0
C, d, v are the constant in Qw function expressions；Obtain Qw function expression be：QW=St* (ρ * u) (H0-Hw),
St is because of Margoulis number.
The present invention is had the advantage that compared with prior art：
(1) modeling method practicality of the invention is high, in modeling process, the letter of the unified heat flux distribution rule of reflection
Number is produced by functional optimized algorithm, and |input paramete only reflects the high accuracy differentiation Aerodynamic Heating of different physical mechanisms
Test data, it is not necessary to other manual interventions.The one-sidedness of prior art modeling method is avoided, artificial sense datum is reduced
Interference.
(2) model obtained using the present invention has more preferable terseness.The functional algorithm of the present invention is in optimization process
Overall balance can be carried out between data residual sum model complexity, succinct mathematical function analytical expression is obtained.
(3) model obtained using the present invention has more preferable versatility, by the test data of multiple wind-tunnel, it is ensured that
The orthogonality of data, it is ensured that the high-adaptability of model.The coverage of present invention test is high, to practical flight complexity Airflow Environment
Fully simulate, it is ensured that the precision of prediction of heat flow density in actual flying test.
Description of the drawings
Fig. 1 is the modeling procedure figure of modeling method of the present invention；
Fig. 2 ground experiment point layout schematic diagrames of the present invention；
Heat flux distribution figure before and after Fig. 3 present invention modelings；Wherein Fig. 3 (a) is heat flux distribution figure before modeling；Fig. 3
B () is heat flux distribution figure after modeling.
Specific embodiment
The flow chart of the present invention as shown in figure 1, carry out the point of different contracting ratios first in different types of hypersonic wind tunnel
Cone calorimetric test, obtains the high accuracy differentiation aerothermodynamics experiment data of the different physical mechanisms of reflection, and draws different tests
Heat flux distribution rule, judges whether rule is unified, if disunity, carries out spatial alternation under the guidance of functional optimization,
Continuous iteration, until obtaining the unified regularity of distribution.
The specific implementation step of the present invention is given with reference to instantiation：
(1) using hypersonic calorimetric wind-tunnel, ground calorimetric is carried out to the pointed cone model of two different contracting ratios of aircraft
Test.Two kinds are contracted than pointed cone model as shown in Fig. 2 calorimetric test is carried out in wind-tunnel 1,2, wherein test model for semi-cone angle is
7 degree of pointed cone, 1 length L=571mm of model arrange 17 measuring points, and 2 length L=1136mm of model arranges 37 measuring points.
Obtain heat flow density data of the different scale models under different wind-tunnel difference operating mode.Wherein, the trystate of wind-tunnel 1 is H0=
16MJ/kg, u=4979m/s, Thermochemical Non-equilibrium state；The trystate of wind-tunnel 2 be H0=3.3MJ/kg, u=2343m/s,
Calorimetric ideal gas.
(2) obtain heat flux distribution rule of two different scale models in hypersonic calorimetric wind-tunnel respectively to obtain
Heat flow density test value Qw1 and Qw2；
(3) adjust j-1 hypersonic calorimetric wind-tunnel wind tunnel test parameter, including wind-tunnel stagnation temperature T0, wind-tunnel stagnation pressure P0,
Wind-tunnel total enthalpy H0, wind-tunnel wall enthalpy Hw, incoming-flow pressure p, come current density ρ, velocity vector u, Mach number M, unit reynolds number Re L,
Local reynolds number Re x, obtains first group of heat flow density test value Qw1j and Qw2j；
(4) using existing modeling method, obtain heat flux distribution rule Qw1=fij of first group of aircraft1(T0,
P0, H0, Hw, p, ρ, u, M, ReL, Rex), wherein T0 is wind-tunnel stagnation temperature, P0 is wind-tunnel stagnation pressure, H0 is wind-tunnel total enthalpy, Hw is wind-tunnel
Wall enthalpy, p be incoming-flow pressure, ρ be come current density, u for velocity vector, M be Mach number, ReL be unit Reynolds number, Rex be to work as
Ground Reynolds number；
(5) k-1 different hypersonic calorimetric wind-tunnel is changed, repeat step (1)-(4) obtain k group aircraft altogether
Heat flux distribution rule Qwk=fijk(T0, P0, H0, Hw, p, ρ, u, M, ReL, Rex), type of wind tunnel should cover shock tunnel
And gun wind tunnel.
(6) using functional optimized algorithm, wind-tunnel qualitative variables a and mark mould parameter b is introduced, calculating is iterated to Qwk, is asked
The spatial alternation of optimum is taken, pointed cone heat flow density model Qw=f (T0, P0, H0, Hw, p, ρ, u, M, ReL, Rex, a, b) is obtained.
The function representation form with least complex is sought using functional optimized algorithm in function space；K group numbers
According to Qwk=fijk(T0, P0, H0, Hw, p, ρ, u, M, ReL, Rex), substitutes into formula
Search in canonical function storehouse, withValue most approach 0 for optimal function form.
F (t) is default solved function form, f (t)=f (T0, P0, H0, Hw, p, ρ, u, M, ReL, Rex, a, b)；g
T () is canonical function form；For f (t), g (t) Hilbert space angle.
Most match canonical function form g (t) and there is following relation with Qw：
C+d/ (v+Rex)-Qw/ (ρ * u) (H0-Hw)=0
C, d, v are the constant in Qw function expressions.
Because Margoulis number expression formula is：
St=Qw/ (ρ * u) is (H0-Hw)
Therefore, St=c+d/ (v+Rex)
Try to achieve：
C=8.223e-4, d=220.1, v=3158.
Try to achieve QW=St* (ρ * u) (H0-Hw).
Shown in heat flux distribution rule such as Fig. 3 (b) after modeling, heat flux distribution figure such as Fig. 3 (a) institutes before modeling
Show, the contrast of two width figures this it appears that only can express the heat flux distribution rule of two wind-tunnel by a function after modeling
Rule.
(7) carry out calculating the calculating data of acquisition according to Qw=f (t), and actual flying test Data Comparison, when meeting essence
When degree is required, Qw function expressions are determined；When precision is unsatisfactory for required precision, return to step (6) regains the function of Qw
Expression formula.
The pointed cone profile heat flux distribution model that the hypersonic wind tunnel modeling method of the present invention is obtained is applied to superb
In the Aerodynamic Heating high-precision forecast of velocity of sound flight, the heat flux distribution rule of Accurate Prediction aircraft outer surface different parts
Rule, precision of prediction are high, and complexity is low, and forecasting efficiency is high.
The above, optimal specific embodiment only of the invention, but protection scope of the present invention is not limited thereto,
Any those familiar with the art the invention discloses technical scope in, the change or replacement that can be readily occurred in,
Should all be included within the scope of the present invention.
The content not being described in detail in description of the invention belongs to the known technology of professional and technical personnel in the field.
Claims (5)
1. a kind of hypersonic pointed cone profile heat flow density modeling method optimized based on functional, it is characterised in that including following step
Suddenly：
(1) using hypersonic calorimetric wind-tunnel, ground calorimetric test is carried out to the pointed cone model of n different contracting ratios of aircraft；
(2) heat flux distribution rule of the n different scale models in hypersonic calorimetric wind-tunnel is obtained respectively obtains hot-fluid
Density test value Qwi, wherein 1≤i≤n；
(3) the wind tunnel test parameter of hypersonic calorimetric wind-tunnel is adjusted, first group of heat flow density test value Qwij is obtained, j is wind
Hole test number (TN)；
(4) obtain heat flux distribution rule Qw1=fij of first group of aircraft1(T0,P0,H0,Hw,p,ρ,u,M,ReL,
Rex), wherein T0 be wind-tunnel stagnation temperature, P0 be wind-tunnel stagnation pressure, H0 be wind-tunnel total enthalpy, Hw be wind-tunnel wall enthalpy, p be incoming-flow pressure, ρ
For come current density, u for velocity vector, M be Mach number, ReL be unit Reynolds number, Rex be local Reynolds number；
(5) k-1 different hypersonic calorimetric wind-tunnel is changed, repeat step (1)-(4) obtain the hot-fluid of k group aircraft altogether
Density distributing law Qwk=fijk(T0,P0,H0,Hw,p,ρ,u,M,ReL,Rex)；
(6) using functional optimized algorithm, wind-tunnel qualitative variables a and mark mould parameter b is introduced, calculating is iterated to Qwk, is asked for most
Excellent spatial alternation, obtains the expression formula of pointed cone heat flow density model Qw=f (t).
2. the hypersonic pointed cone profile heat flow density modeling method for being optimized based on functional as claimed in claim 1, its feature
It is, also including step (7), to carry out calculating according to Qw=f (t) the calculating data of acquisition, and actual flying test Data Comparison,
When required precision is met, Qw function expressions are determined；When precision is unsatisfactory for required precision, return to step (6) is regained
The function expression of Qw.
3. the hypersonic pointed cone profile heat flow density modeling method for being optimized based on functional as claimed in claim 1, its feature
It is that k different hypersonic calorimetric wind-tunnel includes shock tunnel and gun wind tunnel.
4. the hypersonic pointed cone profile heat flow density modeling method for being optimized based on functional as claimed in claim 1, its feature
It is in step (6), to apply functional optimized algorithm, introduces wind-tunnel qualitative variables a and mark mould parameter b, meter is iterated to Qwk
Calculate, the concrete grammar for obtaining pointed cone heat flow density calculating model Qw is：Tool is sought using functional optimized algorithm in function space
There are f (t) the function representation forms of least complex.
5. the hypersonic pointed cone profile heat flow density modeling method for being optimized based on functional as claimed in claim 4, its feature
It is to seek the concrete side of f (t) the function representation forms with least complex in function space using functional optimized algorithm
Method is：Using heat flux distribution rule Qwk=fij of k group aircraftk(T0, P0, H0, Hw, p, ρ, u, M, ReL, Rex), generation
Enter formulaMost adaptation function form g (t) is searched in canonical function storehouse；
F (t) is default solved function form；G (t) is canonical function form；It is f (t), g (t) in Hilbert space
Angle；
G (t) and Qw has following relation：
C+d/ (v+Rex)-Qw/ (ρ * u) (H0-Hw)=0
C, d, v are the constant in Qw function expressions；Obtain Qw function expression be：(H0-Hw), St is QW=St* (ρ * u)
Because of Margoulis number.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610955734.4A CN106528990B (en) | 2016-10-27 | 2016-10-27 | A kind of hypersonic pointed cone shape heat flow density modeling method based on functional optimization |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610955734.4A CN106528990B (en) | 2016-10-27 | 2016-10-27 | A kind of hypersonic pointed cone shape heat flow density modeling method based on functional optimization |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106528990A true CN106528990A (en) | 2017-03-22 |
| CN106528990B CN106528990B (en) | 2019-08-09 |
Family
ID=58326860
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610955734.4A Active CN106528990B (en) | 2016-10-27 | 2016-10-27 | A kind of hypersonic pointed cone shape heat flow density modeling method based on functional optimization |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106528990B (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107808065A (en) * | 2017-11-23 | 2018-03-16 | 南京航空航天大学 | The solid hot quick calculation method of 3 D complex profile high-speed aircraft stream |
| CN109856177A (en) * | 2017-11-30 | 2019-06-07 | 中国飞机强度研究所 | A kind of aircraft protective cover thermal release experimental rig |
| CN112001034A (en) * | 2020-09-09 | 2020-11-27 | 中国空气动力研究与发展中心计算空气动力研究所 | Multi-surface cone-shaped flight wind tunnel model layout and design method |
| CN112378617A (en) * | 2020-12-09 | 2021-02-19 | 中国航天空气动力技术研究院 | Data processing method for eliminating interference of pulse wind tunnel heat measuring signal |
| CN114528645A (en) * | 2022-04-24 | 2022-05-24 | 中国空气动力研究与发展中心超高速空气动力研究所 | Design method of hypersonic velocity aerodynamic thermal standard model for simulating three-dimensional complex flow |
| CN115312139A (en) * | 2022-09-23 | 2022-11-08 | 中国空气动力研究与发展中心计算空气动力研究所 | Method for accessing and converting hypersonic flow chemical reaction model data |
| CN117782515A (en) * | 2024-02-28 | 2024-03-29 | 中国空气动力研究与发展中心计算空气动力研究所 | Aerodynamic heat data uncertainty evaluation method for impact of shock tunnel inflow parameters |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000334055A (en) * | 1999-05-26 | 2000-12-05 | Fujita Corp | Safety evaluation method of fire escape and media to record its safety evaluation program |
| CN103942401A (en) * | 2014-05-14 | 2014-07-23 | 哈尔滨工业大学 | Tool kit and method for optimizing high-precision self-adaptation and modular spacecraft trajectory multi-constrained track |
-
2016
- 2016-10-27 CN CN201610955734.4A patent/CN106528990B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000334055A (en) * | 1999-05-26 | 2000-12-05 | Fujita Corp | Safety evaluation method of fire escape and media to record its safety evaluation program |
| CN103942401A (en) * | 2014-05-14 | 2014-07-23 | 哈尔滨工业大学 | Tool kit and method for optimizing high-precision self-adaptation and modular spacecraft trajectory multi-constrained track |
Non-Patent Citations (4)
| Title |
|---|
| H. KNAUSS 等: "CALIBRATION EXPERIMENTS OF A NEW ACTIVE FAST RESPONSE HEAT FLUX SENSOR TO MEASURE TOTAL TEMPERATURE FLUCTUATIONS", 《PART III. HEAT FLUX DENSITY DETERMINATION IN A SHORT DURATION WIND TUNNEL》 * |
| 姚恩亮: "超声速球锥型飞行器气动热数值计算与研究", 《中国优秀硕士学位论文全文数据库》 * |
| 姜宗林 等: "高超声速风洞实验数据的多维空间相关理论与关联方法", 《中国科学：物理学 力学 天文学》 * |
| 孙翼 等: "发汗冷却控制模型边界热流密度的辨识方法", 《系统工程与电子技术》 * |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107808065A (en) * | 2017-11-23 | 2018-03-16 | 南京航空航天大学 | The solid hot quick calculation method of 3 D complex profile high-speed aircraft stream |
| CN109856177A (en) * | 2017-11-30 | 2019-06-07 | 中国飞机强度研究所 | A kind of aircraft protective cover thermal release experimental rig |
| CN109856177B (en) * | 2017-11-30 | 2021-04-20 | 中国飞机强度研究所 | Aircraft safety cover thermal separation test device |
| CN112001034A (en) * | 2020-09-09 | 2020-11-27 | 中国空气动力研究与发展中心计算空气动力研究所 | Multi-surface cone-shaped flight wind tunnel model layout and design method |
| CN112001034B (en) * | 2020-09-09 | 2022-03-29 | 中国空气动力研究与发展中心计算空气动力研究所 | Multi-surface cone-shaped flight wind tunnel model layout and design method |
| CN112378617B (en) * | 2020-12-09 | 2023-03-07 | 中国航天空气动力技术研究院 | Data processing method for eliminating interference of pulse wind tunnel heat measuring signal |
| CN112378617A (en) * | 2020-12-09 | 2021-02-19 | 中国航天空气动力技术研究院 | Data processing method for eliminating interference of pulse wind tunnel heat measuring signal |
| CN114528645A (en) * | 2022-04-24 | 2022-05-24 | 中国空气动力研究与发展中心超高速空气动力研究所 | Design method of hypersonic velocity aerodynamic thermal standard model for simulating three-dimensional complex flow |
| CN114528645B (en) * | 2022-04-24 | 2022-07-01 | 中国空气动力研究与发展中心超高速空气动力研究所 | Design method of hypersonic velocity aerodynamic thermal standard model for simulating three-dimensional complex flow |
| CN115312139A (en) * | 2022-09-23 | 2022-11-08 | 中国空气动力研究与发展中心计算空气动力研究所 | Method for accessing and converting hypersonic flow chemical reaction model data |
| CN115312139B (en) * | 2022-09-23 | 2023-01-13 | 中国空气动力研究与发展中心计算空气动力研究所 | Method for accessing and converting hypersonic flow chemical reaction model data |
| CN117782515A (en) * | 2024-02-28 | 2024-03-29 | 中国空气动力研究与发展中心计算空气动力研究所 | Aerodynamic heat data uncertainty evaluation method for impact of shock tunnel inflow parameters |
| CN117782515B (en) * | 2024-02-28 | 2024-05-07 | 中国空气动力研究与发展中心计算空气动力研究所 | Aerodynamic heat data uncertainty evaluation method for impact of shock tunnel inflow parameters |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106528990B (en) | 2019-08-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106528990A (en) | Hypersonic velocity pointed conical appearance heat flux density modeling approach based on functional optimization | |
| Marvin | Perspective on computational fluid dynamics validation | |
| Vidanović et al. | Validation of the CFD code used for determination of aerodynamic characteristics of nonstandard AGARD-B calibration model | |
| Zhao et al. | Uncertainty and sensitivity analysis of flow parameters for transition models on hypersonic flows | |
| Nichols et al. | Input-output analysis of complex hypersonic boundary layers | |
| Koupper et al. | Experimental and numerical calculation of turbulent timescales at the exit of an engine representative combustor simulator | |
| Edquist et al. | Computational Modeling of Mars Retropropulsion Concepts in the Langley Unitary Plan Wind Tunnel | |
| Georgiadis et al. | Mach Number and Heating Effects on Turbulent Supersonic Jets | |
| CN114462336B (en) | Method for calculating average temperature of coolant of main pipeline of nuclear reactor | |
| CN111563297A (en) | Supersonic aircraft thermal environment calculation method based on BP network | |
| Ferrero et al. | A numerical method for conjugate heat transfer problems in hypersonic flows | |
| Schneider | Computational modeling of total temperature probes | |
| Hoopes | A new method for generating swirl inlet distortion for jet engine research | |
| Dreyer et al. | Towards characterization of relevant fidelity modeling of loads for maneuvering hypersonic vehicles | |
| Carnduff | Flight Vehicle System Identification: a Time-Domain Methodology–Second edition Progress in Aeronautics and Astronautics Vol 245R. V. Jategaonkar American Institute of Aeronautics and Astronautics, 1801 Alexander Bell Drive, Suite 500, Reston, VA, 20191-4344, USA. 2014. 627pp. Illustrated. $119.95. ISBN 978-1-62410-278-3. | |
| Chauchat et al. | Cooling of a heating cylinder by confined impacting air jets | |
| Brown et al. | Fluid mechanics in a radiatively driven hypersonic wind tunnel-Prediction and preliminary experiment | |
| Mern et al. | A study of numerical simulation of supersonic conical nozzle exhaust | |
| Granados-Ortiz et al. | A novel framework for uncertainty propagation in multidisciplinary design life cycle for shock-cell noise research | |
| Morris et al. | Uncertainty propagation via Monte Carlo simulation in the PWT and VKF wind tunnels at AEDC | |
| Verma et al. | Numerical and experimental investigation of flow in an open-type subsonic wind tunnel | |
| Jiang et al. | Application of Characteristic Model-Based Principal Component Analysis in Optimization of Flowmeter Parameters | |
| Matesanz et al. | Numerical simulation of base-flow/plume interaction | |
| Meritt et al. | Direct Skin Friction Measurements at Mach 14 in AEDC Hypervelocity Wind Tunnel 9 | |
| Doom et al. | Verification and Validation of a Small Wind Tunnel Data Acquisition System |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |