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NASA NTRS1982

Environmental and high strain rate effects on composites for engine applications

The complex environmental and loading conditions experienced by many turbine engine components impose severe durability and damage tolerance requirements for component materials. Programs are being conducted to establish the structural performance of composite materials under anticipated engine operating environments. A description is presented of the results obtained in connection with several of these programs. A comparison of predicted and measured hygrothermal effects is considered along with hygrothermal effects on defect growth, high strain rate effects on composite mechanical properties, dynamic stress intensity factors for composites, and the indentation laws for composite impact analysis.

Chamis, C. C.↗

NASA NTRS2001

The AutoBayes Program Synthesis System: System Description

AUTOBAYES is a fully automatic program synthesis system for the statistical data analysis domain. Its input is a concise description of a data analysis problem in the form of a statistical model; its output is optimized and fully documented C/C++ code which can be linked dynamically into the Matlab and Octave environments. AUTOBAYES synthesizes code by a schema-guided deductive process. Schemas (i.e., code templates with associated semantic constraints) are applied to the original problem and recursively to emerging subproblems. AUTOBAYES complements this approach by symbolic computation to derive closed-form solutions whenever possible. In this paper, we concentrate on the interaction between the symbolic computations and the deductive synthesis process. A statistical model specifies for each problem variable (i.e., data or parameter) its properties and dependencies in the form of a probability distribution, A typical data analysis task is to estimate the best possible parameter values from the given observations or measurements. The following example models normal-distributed data but takes prior information (e.g., from previous experiments) on the data's mean value and variance into account.

Fischer, Bernd↗

NASA NTRS2002

Opportunities for Breakthroughs in Large-Scale Computational Simulation and Design

Opportunities for breakthroughs in the large-scale computational simulation and design of aerospace vehicles are presented. Computational fluid dynamics tools to be used within multidisciplinary analysis and design methods are emphasized. The opportunities stem from speedups and robustness improvements in the underlying unit operations associated with simulation (geometry modeling, grid generation, physical modeling, analysis, etc.). Further, an improved programming environment can synergistically integrate these unit operations to leverage the gains. The speedups result from reducing the problem setup time through geometry modeling and grid generation operations, and reducing the solution time through the operation counts associated with solving the discretized equations to a sufficient accuracy. The opportunities are addressed only at a general level here, but an extensive list of references containing further details is included. The opportunities discussed are being addressed through the Fast Adaptive Aerospace Tools (FAAST) element of the Advanced Systems Concept to Test (ASCoT) and the third Generation Reusable Launch Vehicles (RLV) projects at NASA Langley Research Center. The overall goal is to enable greater inroads into the design process with large-scale simulations.

Alexandrov, Natalia↗

NASA NTRS2003

Experiments with Test Case Generation and Runtime Analysis

Software testing is typically an ad hoc process where human testers manually write many test inputs and expected test results, perhaps automating their execution in a regression suite. This process is cumbersome and costly. This paper reports preliminary results on an approach to further automate this process. The approach consists of combining automated test case generation based on systematically exploring the program's input domain, with runtime analysis, where execution traces are monitored and verified against temporal logic specifications, or analyzed using advanced algorithms for detecting concurrency errors such as data races and deadlocks. The approach suggests to generate specifications dynamically per input instance rather than statically once-and-for-all. The paper describes experiments with variants of this approach in the context of two examples, a planetary rover controller and a space craft fault protection system.

Artho, Cyrille↗

NASA NTRS1987

Challenges in modeling the X-29A flight test performance

The paper presents the methods, instrumentation, and difficulties associated with drag measurement of the X-29A aircraft. The initial performance objective of the X-29A program emphasized drag polar shapes rather than absolute drag levels. Priorities during the flight envelope expansion restricted the evaluation of aircraft performance. Changes in aircraft configuration, uncertainties in angle-of-attack calibration, and limitations in instrumentation complicated the analysis. Limited engine instrumentation with uncertainties in overall in-flight thrust accuracy made it difficult to obtain reliable values of coefficient of parasite drag. The aircraft was incapable of tracking the automatic camber control trim schedule for optimum wing flaperon deflection during typical dynamic performance maneuvers; this has also complicated the drag polar shape modeling. The X-29A was far enough off the schedule that the developed trim drag correction procedure has proven inadequate. Despite these obstacles, good drag polar shapes have been developed throughout the flight envelope. Preliminary flight results have compared well with wind tunnel predictions. A more comprehensive analysis must be done to complete the performance models. The detailed flight performance program with a calibrated engine will benefit from the experience gained during this preliminary performance phase.

Hicks, John W.↗

DOE OSTI2022

Estimating epistemic uncertainty in soil parameters for nonlinear site response analyses: Introducing the Latin Hypercube Sampling technique

This study quantifies the effects of epistemic uncertainty in soil parameters on nonlinear (NL) site response analysis (SRA) results, validated against the data recorded at a well-instrumented geotechnical downhole array located in Japan. To this end, a one-dimensional soil column model of the Service Hall Array (SHA) near the Kashiwazaki-Kariwa Nuclear Power Plant (KKNPP) is developed using the finite element (FE) program LS-DYNA. The dynamic stress–strain relationship is characterized by a modified two-stage hyperbolic (MTH) NL backbone curve formulation capable of capturing soil behavior at both small- and large-shear strains. The model is then validated against the ground motion recordings to capture the model bias. The uncertainties associated with the shear-wave velocity profile (a small-strain soil property) and soil shear strength (a large-strain soil property) are incorporated in NL SRA to quantify their separate and joint randomization effects on the results. This study proposes using the Latin Hypercube Sampling (LHS) method as an efficient alternative to commonly used methods, such as Standard Monte Carlo (SMC), to account for uncertainty propagation in such reliability analysis. Both low-intensity and design-level records from the recordings at the SHA are applied to study the contribution of the small- and large-strain NL dynamic soil properties. Results from 46,200 NL FE analyses (23,100 per input motion) are presented. Measured and predicted site response, using recorded ground motions at this downhole array, is compared to assess the significance of soil parameter uncertainty on the observed ground motion dispersions. It is demonstrated that increasing the number of soft realizations and implementing higher level earthquake intensity lead to higher ground motion dispersion. Unlike past studies in randomization of Vs profiles with the SMC method, the LHS method is shown to have no significant effect on the predicted median surface response spectra and amplification factors (AFs) for this case study.

Engineering↗

NASA NTRS1976

Abort Region Determinator (ARD) module feasibility report. Mission planning, mission analysis and software formulation

A detailed performance evaluation of the Abort Region Determinator (ARD) module design was provided in support of OFT-1 ascent and OFT-1 intact launch aborts. The evaluation method used compared ARD results against results obtained using the full-up Space Vehicle Dynamic Simulations program under the same conditions. Results were presented for each of the three major ARD math models: (1) the ascent numerical integrator; (2) the mass model, and (3) the second stage predictor as well as the total ARD module. These results demonstrate that the baselined ARD module meets all design objectives for mission control center orbital flight test launch/abort support.

Draeger, B. G.↗

NASA NTRS1992

Interplanetary Program to Optimize Simulated Trajectories (IPOST). Volume 1: User's guide

IPOST is intended to support many analysis phases, from early interplanetary feasibility studies through spacecraft development and operations. The IPOST output provides information for sizing and understanding mission impacts related to propulsion, guidance, communications, sensor/actuators, payload, and other dynamic and geometric environments. IPOST models three degree of freedom trajectory events, such as launch/ascent, orbital coast, propulsive maneuvering (impulsive and finite burn), gravity assist, and atmospheric entry. Trajectory propagation is performed using a choice of Cowell, Encke, Multiconic, Onestep, or Conic methods. The user identifies a desired sequence fo trajectory events, and selects which parameters are independent (controls) and dependent (targets), as well as other constraints and the coat function. Targeting and optimization is performed using the Stanford NPSOL algorithm. IPOST structure allows sub-problems within a master optimization problem to aid in the general constrained parameter optimization solution. An alternate optimization method uses implicit simulation and collocation techniques.

Hong, P. E.↗

NASA NTRS1995

Computational fluid dynamic analysis of hybrid rocket combustor flowfields

Computational fluid dynamic analyses of the Navier-Stokes equations coupled with solid-phase pyrolysis, gas-phase combustion, turbulence and radiation are performed to study hybrid rocket combustor flowfields. The computational study is closely co-ordinated with a companion experimental program using a planar slab burner configuration with HTPB as fuel and gaseous oxygen. Computational predictions agree reasonably well with measurement data of fuel regression rates and surface temperatures. Additionally, most of the parametric trends predicted by the model are in general agreement with experimental trends. The computational model is applied to extend the results from the lab-scale to a full-scale axisymmetric configuration. The numerical predictions indicate that the full-scale configuration burns at a slower rate than the lab-scale combustor under identical specific flow rate conditions. The results demonstrate that detailed CFD analyses can play a useful role in the design of hybrid combustors.

Venkateswaran, S.↗

DOE OSTI2017

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analy- sis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncer- tainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is in- terested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assess- ment capability to RELAP-7, currently under develop-ment at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explaination of the input requirements, focalizing on the input structure.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

RAVEN User Manual

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1975

DC-9 Flight Demonstration Program with Refanned JT8D Engines: Performance and Analysis - Volume 3

The JT8D-109 engine has a sea level static, standard day bare engine takeoff thrust of 73,840 N. At sea level standard day conditions the additional thrust of the JT8D-109 results in 2,040 kg additional takeoff gross weight capability for a given field length. Range loss of the DC-9 Refan airplane for long range cruise was determined. The Refan airplane demonstrated stall, static longitudinal stability, longitudinal control, longitudinal trim, minimum control speeds, and directional control characteristics similar to the DC-9-30 production airplane and complied with airworthiness requirements. Cruise, climb, and thrust reverser performance were evaluated. Structural and dynamic ground test, flight test and analytical results substantiate Refan Program requirements that the nacelle, thrust reverser hardware, and the airplane structural modifications are flightworthy and certifiable and that the airplane meets flutter speed margins. Estimated unit cost of a DC-9 Refan retrofit program is 1.338 million in mid-1975 dollars with about an equal split in cost between airframe and engine.

Source record↗

NASA NTRS1990

Staggered solution procedures for multibody dynamics simulation

The numerical solution procedure for multibody dynamics (MBD) systems is termed a staggered MBD solution procedure that solves the generalized coordinates in a separate module from that for the constraint force. This requires a reformulation of the constraint conditions so that the constraint forces can also be integrated in time. A major advantage of such a partitioned solution procedure is that additional analysis capabilities such as active controller and design optimization modules can be easily interfaced without embedding them into a monolithic program. After introducing the basic equations of motion for MBD system in the second section, Section 3 briefly reviews some constraint handling techniques and introduces the staggered stabilized technique for the solution of the constraint forces as independent variables. The numerical direct time integration of the equations of motion is described in Section 4. As accurate damping treatment is important for the dynamics of space structures, we have employed the central difference method and the mid-point form of the trapezoidal rule since they engender no numerical damping. This is in contrast to the current practice in dynamic simulations of ground vehicles by employing a set of backward difference formulas. First, the equations of motion are partitioned according to the translational and the rotational coordinates. This sets the stage for an efficient treatment of the rotational motions via the singularity-free Euler parameters. The resulting partitioned equations of motion are then integrated via a two-stage explicit stabilized algorithm for updating both the translational coordinates and angular velocities. Once the angular velocities are obtained, the angular orientations are updated via the mid-point implicit formula employing the Euler parameters. When the two algorithms, namely, the two-stage explicit algorithm for the generalized coordinates and the implicit staggered procedure for the constraint Lagrange multipliers, are brought together in a staggered manner, they constitute a staggered explicit-implicit procedure which is summarized in Section 5. Section 6 presents some example problems and discussions concerning several salient features of the staggered MBD solution procedure are offered in Section 7.

Park, K. C.↗

NASA NTRS2009

Impact Testing on Reinforced Carbon-Carbon Flat Panels with Ice Projectiles for the Space Shuttle Return to Flight Program

Following the tragedy of the Orbiter Columbia (STS-107) on February 1, 2003, a major effort commenced to develop a better understanding of debris impacts and their effect on the space shuttle subsystems. An initiative to develop and validate physics-based computer models to predict damage from such impacts was a fundamental component of this effort. To develop the models it was necessary to physically characterize reinforced carbon-carbon (RCC) along with ice and foam debris materials, which could shed on ascent and impact the orbiter RCC leading edges. The validated models enabled the launch system community to use the impact analysis software LS-DYNA (Livermore Software Technology Corp.) to predict damage by potential and actual impact events on the orbiter leading edge and nose cap thermal protection systems. Validation of the material models was done through a three-level approach: Level 1--fundamental tests to obtain independent static and dynamic constitutive model properties of materials of interest, Level 2--subcomponent impact tests to provide highly controlled impact test data for the correlation and validation of the models, and Level 3--full-scale orbiter leading-edge impact tests to establish the final level of confidence for the analysis methodology. This report discusses the Level 2 test program conducted in the NASA Glenn Research Center (GRC) Ballistic Impact Laboratory with ice projectile impact tests on flat RCC panels, and presents the data observed. The Level 2 testing consisted of 54 impact tests in the NASA GRC Ballistic Impact Laboratory on 6- by 6-in. and 6- by 12-in. flat plates of RCC and evaluated three types of debris projectiles: Single-crystal, polycrystal, and "soft" ice. These impact tests helped determine the level of damage generated in the RCC flat plates by each projectile and validated the use of the ice and RCC models for use in LS-DYNA.

Melis, Matthew E.↗

NASA NTRS2009

Impact Testing on Reinforced Carbon-Carbon Flat Panels With BX-265 and PDL-1034 External Tank Foam for the Space Shuttle Return to Flight Program

Following the tragedy of the Orbiter Columbia (STS-107) on February 1, 2003, a major effort commenced to develop a better understanding of debris impacts and their effect on the space shuttle subsystems. An initiative to develop and validate physics-based computer models to predict damage from such impacts was a fundamental component of this effort. To develop the models it was necessary to physically characterize reinforced carbon-carbon (RCC) along with ice and foam debris materials, which could shed on ascent and impact the orbiter RCC leading edges. The validated models enabled the launch system community to use the impact analysis software LS-DYNA (Livermore Software Technology Corp.) to predict damage by potential and actual impact events on the orbiter leading edge and nose cap thermal protection systems. Validation of the material models was done through a three-level approach: Level 1-fundamental tests to obtain independent static and dynamic constitutive model properties of materials of interest, Level 2-subcomponent impact tests to provide highly controlled impact test data for the correlation and validation of the models, and Level 3-full-scale orbiter leading-edge impact tests to establish the final level of confidence for the analysis methodology. This report discusses the Level 2 test program conducted in the NASA Glenn Research Center (GRC) Ballistic Impact Laboratory with external tank foam impact tests on flat RCC panels, and presents the data observed. The Level 2 testing consisted of 54 impact tests in the NASA GRC Ballistic Impact Laboratory on 6- by 6-in. and 6- by 12-in. flat plates of RCC and evaluated two types of debris projectiles: BX-265 and PDL-1034 external tank foam. These impact tests helped determine the level of damage generated in the RCC flat plates by each projectile and validated the use of the foam and RCC models for use in LS-DYNA.

Melis, Matthew E.↗

NASA NTRS1999

Overview of Fluid Dynamics Activities at the Marshall Space Flight Center

Since its inception 40 years ago, Marshall Space Flight Center (MSFC) has had the need to maintain and advance state-of-the-art flow analysis and cold-flow testing capability to support its roles and missions. This overview discusses the recent organizational changes that have occurred at MSFC with emphasis on the resulting three groups that form the core of fluid dynamics expertise at MSFC: the Fluid Physics and Dynamics Group, the Applied Fluid Dynamics Analysis Group, and the Experimental Fluid Dynamics Group. Recently completed activities discussed include the analysis and flow testing in support of the Fastrac engine design, the X-33 vehicle design, and the X34 propulsion system design. Ongoing activities include support of the RLV vehicle design, Liquid Fly Back Booster aerodynamic configuration definition, and RLV focused technologies development. Other ongoing activities discussed are efforts sponsored by the Center Director's Discretionary Fund (CDDF) to develop an advanced incompressible flow code and to develop optimization techniques. Recently initiated programs and their anticipated required fluid dynamics support are discussed. Based on recent experiences and on the anticipated program needs, required analytical and experimental technique improvements are presented. Due to anticipated budgetary constraints, there is a strong need to leverage activities and to pursue teaming arrangements in order to advance the state-of-the-art and to adequately support concept development. Throughout this overview there is discussion of the lessons learned and of the capabilities demonstrated and established in support of the hardware development programs.

Garcia, Roberto↗

DOE OSTI2014

RAVEN and Dynamic Probabilistic Risk Assessment: Software overview

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7 [], currently under development at the Idaho National Laboratory. Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism has been employed by providing Application Programming Interfaces (APIs). These interfaces are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable to investigate the system response, investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The paper presents an overview of the software capabilities and their implementation schemes followed by some application examples.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2015

SU-E-T-255: Development of a Michigan Quality Assurance (MQA) Database for Clinical Machine Operations

Purpose: A unified database system was developed to allow accumulation, review and analysis of quality assurance (QA) data for measurement, treatment, imaging and simulation equipment in our department. Recording these data in a database allows a unified and structured approach to review and analysis of data gathered using commercial database tools. Methods: A clinical database was developed to track records of quality assurance operations on linear accelerators, a computed tomography (CT) scanner, high dose rate (HDR) afterloader and imaging systems such as on-board imaging (OBI) and Calypso in our department. The database was developed using Microsoft Access database and visual basic for applications (VBA) programming interface. Separate modules were written for accumulation, review and analysis of daily, monthly and annual QA data. All modules were designed to use structured query language (SQL) as the basis of data accumulation and review. The SQL strings are dynamically re-written at run time. The database also features embedded documentation, storage of documents produced during QA activities and the ability to annotate all data within the database. Tests are defined in a set of tables that define test type, specific value, and schedule. Results: Daily, Monthly and Annual QA data has been taken in parallel with established procedures to test MQA. The database has been used to aggregate data across machines to examine the consistency of machine parameters and operations within the clinic for several months. Conclusion: The MQA application has been developed as an interface to a commercially available SQL engine (JET 5.0) and a standard database back-end. The MQA system has been used for several months for routine data collection.. The system is robust, relatively simple to extend and can be migrated to a commercial SQL server.

60 APPLIED LIFE SCIENCES↗