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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Size Effects in Impact Damage of Composite Sandwich Panels

Panel size has a large effect on the impact response and resultant damage level of honeycomb sandwich panels. It has been observed during impact testing that panels of the same design but different panel sizes will show large differences in damage when impacted with the same impact energy. To study this effect, a test program was conducted with instrumented impact testing of three different sizes of sandwich panels to obtain data on panel response and residual damage. In concert with the test program. a closed form analysis method was developed that incorporates the effects of damage on the impact response. This analysis method will predict both the impact response and the residual damage of a simply-supported sandwich panel impacted at any position on the panel. The damage is incorporated by the use of an experimental load-indentation curve obtained for the face-sheet/honeycomb and indentor combination under study. This curve inherently includes the damage response and can be obtained quasi-statically from a rigidly-backed specimen or a specimen with any support conditions. Good correlation has been obtained between the test data and the analysis results for the maximum force and residual indentation. The predictions can be improved by using a dynamic indentation curve. Analyses have also been done using the MSC/DYTRAN finite element code.

Dobyns, Alan↗
NASA NTRS1989

Error analysis for semi-analytic displacement derivatives with respect to shape and sizing variables

Sensitivity analysis is fundamental to the solution of structural optimization problems. Consequently, much research has focused on the efficient computation of static displacement derivatives. As originally developed, these methods relied on analytical representations for the derivatives of the structural stiffness matrix (K) with respect to the design variables (b sub i). To extend these methods for use with complex finite element formulations and facilitate their implementation into structural optimization programs using the general finite element method analysis codes, the semi-analytic method was developed. In this method the matrix the derivative of K/the derivative b sub i is approximated by finite difference. Although it is well known that the accuracy of the semi-analytic method is dependent on the finite difference parameter, recent work has suggested that more fundamental inaccuracies exist in the method when used for shape optimization. Another study has argued qualitatively that these errors are related to nonuniform errors in the stiffness matrix derivatives. The accuracy of the semi-analytic method is investigated. A general framework was developed for the error analysis and then it is shown analytically that the errors in the method are entirely accounted for by errors in delta K/delta b sub i. Furthermore, it is demonstrated that acceptable accuracy in the derivatives can be obtained through careful selection of the finite difference parameter.

Fenyes, Peter A.↗
NASA NTRS1994

Active magnetic bearing control loop modeling for a finite element rotordynamics code

A mathematical model of an active electromagnetic bearing which includes the actuator, the sensor and the control system is developed and implemented in a specialized finite element code for rotordynamic analysis. The element formulation and its incorporation in the model of the machine are described in detail. A solution procedure, based on a modal approach in which the number of retained modes is controlled by the user, is then shown together with other procedures for computing the steady-state response to both static and unbalance forces. An example of application shows the numerical results obtained on a model of an electric motor suspended on a five active-axis magnetic suspension. The comparison of some of these results with the experimental characteristics of the actual system shows the ability of the present model to predict its performance.

Genta, Giancarlo↗
NASA NTRS1996

Estimation of the longitudinal and lateral-directional aerodynamic parameters from flight data for the NASA F/A-18 HARV

This progress report presents the results of an investigation focused on parameter identification for the NASA F/A-18 HARV. This aircraft was used in the high alpha research program at the NASA Dryden Flight Research Center. In this study the longitudinal and lateral-directional stability derivatives are estimated from flight data using the Maximum Likelihood method coupled with a Newton-Raphson minimization technique. The objective is to estimate an aerodynamic model describing the aircraft dynamics over a range of angle of attack from 5 deg to 60 deg. The mathematical model is built using the traditional static and dynamic derivative buildup. Flight data used in this analysis were from a variety of maneuvers. The longitudinal maneuvers included large amplitude multiple doublets, optimal inputs, frequency sweeps, and pilot pitch stick inputs. The lateral-directional maneuvers consisted of large amplitude multiple doublets, optimal inputs and pilot stick and rudder inputs. The parameter estimation code pEst, developed at NASA Dryden, was used in this investigation. Results of the estimation process from alpha = 5 deg to alpha = 60 deg are presented and discussed.

Napolitano, Marcello R.↗
DOE OSTI2014

Near Real-time Data Analysis of Core-collapse Supernova Simulations with Bellerophon

We present an overview of a software system, Bellerophon, built to support a production-level HPC application called CHIMERA, which simulates core-collapse supernova events at the petascale. Developed over the last four years, Bellerophon enables CHIMERA's geographically dispersed team of collaborators to perform data analysis in near real-time. Its n-tier architecture provides an encapsulated, end-to-end software solution that enables the CHIMERA team to quickly and easily access highly customizable animated and static views of results from anywhere in the world via a web- deliverable, cross-platform desktop application. In addition, Bellerophon addresses software engineering tasks for the CHIMERA team by providing an automated mechanism for performing regression testing on a variety of supercomputing platforms. Elements of the team's workflow management needs are met with software tools that dynamically generate code repository statistics, access important online resources, and monitor the current status of several supercomputing resources.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1999

A High Altitude-Low Reynolds Number Aerodynamic Flight Experiment

A sailplane is currently being developed at NASA's Dryden Flight Research Center to support a high altitude flight experiment. The purpose of the experiment is to measure the performance characteristics of an airfoil at altitudes between 100,000 and 70,000 feet at Mach numbers between 0.65 and 0.5. The airfoil lift and drag are measured from pilot and static pressures. The location of the separation bubble and vortex shedding are measured from a hot film strip. The details of the flight experiment are presented. A comparison of several estimates of the airfoil performance is also presented. The airfoil, APEX-16, was designed by Drela (MIT) with his MSES code. A two dimensional Navier-Stokes analysis has been performed by Tatineni and Zhong (UCLA) and another at the Dryden Flight Research Center. The role these analysis served to define the experiment is discussed.

Greer, Don↗
DOE OSTI2021

Dynamic Probabilistic Safety Assessment Studies for Advanced Reactor Using RAVEN

Probabilistic Safety Assessment (PSA) is used extensively to evaluate the risks associated with complex engineering systems like Nuclear Power Plants (NPPs). Current PSA models are based on the Event-Tree/Fault-Tree (ET/FT) methodology. ET and FT models are static and are based on Boolean logic approaches. In the past, concerns have been raised in the literature regarding the capability of the traditional static modelling approaches to adequately account for the impact of process, hardware, software, firmware and human interactions on the stochastic system behaviour. To overcome the limitations of the traditional approach to PSA, several dynamic PSA methodologies have been proposed. One of the dynamic PSA methodologies used for dynamic evaluations is Dynamic Event Tree (DET) framework which can be used to assess the impact of the parameter variability and scenario dynamics on the PSA model for the initiating event. The DET framework couples the stochastic model (number of component/trains that start on demand, operator action timing, etc.) with a Thermal-Hydraulic (TH) model of the plant. This paper explores the use of DET along with a case study on advanced reactor. The initiating event selected for the study was Class IV power supply failure event. The TH analysis considering uncertainty in various parameters was performed using RELAP5 and Reactor Analysis and Virtual control ENvironment (RAVEN) tool. Based on the uncertainty analysis, it is concluded that the peak clad temperatures (PCT) are within the limits in all the code runs implying a high-degree of safety margin. However, variation in time to reach the PCT was observed among the code runs and the mean time to reach the PCT was found to be around 8590sec (approximately 2.4 hours). Hence, sufficient time margin is available for human intervention and the operator might have a relatively stress-free state during such an accident scenario. Due to the static nature of the traditional PSA models, the safety margin available was lesser, whereas, with the help of dynamic PSA models, one can demonstrate that the actual available safety margin is more in the present case study and is valuable input from the design point of view.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2000

Progress in The Semantic Analysis of Scientific Code

This paper concerns a procedure that analyzes aspects of the meaning or semantics of scientific and engineering code. This procedure involves taking a user's existing code, adding semantic declarations for some primitive variables, and parsing this annotated code using multiple, independent expert parsers. These semantic parsers encode domain knowledge and recognize formulae in different disciplines including physics, numerical methods, mathematics, and geometry. The parsers will automatically recognize and document some static, semantic concepts and help locate some program semantic errors. These techniques may apply to a wider range of scientific codes. If so, the techniques could reduce the time, risk, and effort required to develop and modify scientific codes.

Stewart, Mark↗
DOE OSTI2016

Artificial Neural Network Representation of Dynamic Criticality Excursion Experiment Data

This paper outlines time dependent considerations in applying the artificial neural network (ANN) paradigm to dynamic nuclear criticality excursion experiment data. The ANN amongst a variety of uses, can apply to function fitting of multiple input-multiple output data sets, pattern recognition, cluster analysis, and time series prediction. The ANN is a component of Machine Learning (ML) data analysis. The practical application of ML to criticality safety has been funded through the Y-12 Plant Directed Research and Demonstration (PDRD) program to support criticality safety and emergency planning efforts. The initial effort considered function fitting of criticality excursion data. Recent efforts successfully extended the ANN to criticality safety code validation. The initial ANN work applied to criticality excursions centered around multivariate function fitting of static (tabular) data taken from the French Consequences Radiologiques d'un Accident de Criticite (CRAC) and SILENE reactor campaigns. The former report (LeCorche) summarized important tabular data for the first 44 CRAC experiments. The initial ANN was trained to specific time-independent inputs, then applied to predict peak fission rate and total fissions for a wide variety of fissile solutions process conditions. This work extends that effort to apply the ANN paradigm to dynamic prediction of time-dependent criticality excursion experiment data. A dynamic criticality excursion in fissile solution represents a complex multiphysics phenomenon. Factors include among other things, coupled neutronic, multiphase fluid flow, temperature, pressure, acoustic shock, boiling heat transfer, reactivity feedback, and radiolytic gas considerations. There have been many efforts to model (over time) as coupled ordinary and (space) as partial differential equations (ODE, PDE). The ANN representation noted here does not rely on solving explicit ODE or PDEs. Rather the intent is to demonstrate that as a time series, the criticality excursion can be predicted by training specific ANN architectures to experimental input and output time series exclusively. The rationale for extending this work to the time-dependent regime is important in developing a 'criticality excursion emulator' solely on the basis of learning characteristics from experiment dynamic data. An emulator is different than a computer code simulator driven by the solution of ODEs and PDEs given select 'tuning parameters' that match outputs to experiments. A criticality excursion emulator, derived exclusively from an ANN or ML, could predict most likely excursion characteristics, trained from historic dynamic experiment data, presented with input values within the range of those experiments. The work noted shows that generic time-series ANN architectures can be satisfactorily applied to the prediction of dynamic, extremely chaotic criticality excursion power given an initial time dependent input series. In reality, an excursion emulator could be driven by user-supplied initial (t=0), time independent or constant values to generate time dependent outputs. Thus ongoing work includes developing a custom ANN such that initial dynamic conditions would be predicted. Those results then serve as inputs to a customized ANN architecture currently in development. (author)

42 ENGINEERING↗
DOE OSTI2025

Nuclear Materials Packaging, Transportation, and Systems Analysis Group Software Quality Assurance Plan: ANSYS Mechanical Finite Element Analysis Software Version 2023R1

ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic, and electromagnetic simulation capabilities. ANSYS has two main programs, which use the same solvers: (1) Mechanical APDL (ANSYS Design Parametric Language), a Fortran-based coding platform, and (2) ANSYS Workbench, which uses a graphical user interface to aid in finite element analysis implementation. This plan covers both APDL and Workbench. The ANSYS computer program is a large-scale, multipurpose finite element program that can be used to solve several classes of engineering analyses. The analysis capabilities of ANSYS include the ability to solve static and dynamic structural analyses, steady-state and transient heat transfer problems, mode-frequency and buckling eigenvalue problems, static or time-varying magnetic analyses, and various types of field and coupled-field applications. The program contains many special features that allow nonlinearities or secondary effects such as plasticity, large strain, hyperelasticity, creep, swelling, large deflections, contact, stress stiffening, temperature dependency, material anisotropy, and radiation to be included in the solution. As ANSYS has been developed, other special capabilities such as substructuring, submodeling, random vibration, kinetostatics, kinetodynamics, free convection fluid analysis, acoustics, magnetics, piezoelectrics, coupled-field analysis, and design optimization have been added to the program. These capabilities contribute further to making ANSYS a multipurpose analysis tool for varied engineering disciplines. The ANSYS program has been in commercial use for over 50 years and has been used extensively in the aerospace, automotive, construction, electronic, energy services, manufacturing, nuclear, plastics, oil, and steel industries. Additionally, many consulting firms and hundreds of universities have used ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. Ansys design analysis software is the first created within a quality system with ISO 9001 certification, the internationally accepted quality standard. Product development, testing, maintenance and support processes also meet the United States Nuclear Regulatory Commission's quality requirements, as they have for nearly four decades. The Quality Assurance Service Agreement is suitable for the customers working in the nuclear industry who need to meet specific federal regulations including 10CRF50 Appendix B and provisions of 10CFR21. ANSYS has retained its original International Organization for Standardization (ISO) 9001 accreditation certificate since1995-05-04, It’s current certificate is valid until 2027-05-29.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Neutronic Characteristics of ENDF/B-VIII.0 Compared to ENDF/B-VII.1 for Light-Water Reactor Analysis

The Evaluated Nuclear Data File (ENDF)/B-VIII.0 data library was released in 2018. To assess the new data during development and shortly after release, many validation calculations were performed with static, room-temperature benchmarks. Recently, when performing validation of ENDF/B-VIII.0 for pressurized water reactor depletion calculations, a regression in performance compared to ENDF/B-VII.1 was observed. This paper documents extensive benchmark calculations for light-water reactors performed using continuous energy Monte Carlo code with ENDF/B-VII.1 and -VIII.0 and neutronic characteristics of ENDF/B-VIII.0 are discussed and compared to those of ENDF/B-VII.1. It is our recommendation that ENDF/B data library assessment should include reactor-specific benchmark assessments, including depletion cases, such that these types of regressions may be caught earlier in the data development cycle.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2011

Directed Incremental Symbolic Execution

The last few years have seen a resurgence of interest in the use of symbolic execution -- a program analysis technique developed more than three decades ago to analyze program execution paths. Scaling symbolic execution and other path-sensitive analysis techniques to large systems remains challenging despite recent algorithmic and technological advances. An alternative to solving the problem of scalability is to reduce the scope of the analysis. One approach that is widely studied in the context of regression analysis is to analyze the differences between two related program versions. While such an approach is intuitive in theory, finding efficient and precise ways to identify program differences, and characterize their effects on how the program executes has proved challenging in practice. In this paper, we present Directed Incremental Symbolic Execution (DiSE), a novel technique for detecting and characterizing the effects of program changes. The novelty of DiSE is to combine the efficiencies of static analysis techniques to compute program difference information with the precision of symbolic execution to explore program execution paths and generate path conditions affected by the differences. DiSE is a complementary technique to other reduction or bounding techniques developed to improve symbolic execution. Furthermore, DiSE does not require analysis results to be carried forward as the software evolves -- only the source code for two related program versions is required. A case-study of our implementation of DiSE illustrates its effectiveness at detecting and characterizing the effects of program changes.

Person, Suzette↗
NASA NTRS2014

MicroRNA Expression Profiles in Cultured Human Fibroblasts in Space

Microgravity, or an altered gravity environment from the static 1g, has been shown to influence global gene expression patterns and protein levels in living organisms. However, it is unclear how these changes in gene and protein expressions are related to each other or are related to other factors regulating such changes. A different class of RNA, the small non-coding microRNA (miRNA), can have a broad effect on gene expression networks by mainly inhibiting the translation process. Previously, we investigated changes in the expression of miRNA and related genes under simulated microgravity conditions on the ground using the NASA invented bioreactor. In comparison to static 1 g, simulated microgravity altered a number of miRNAs in human lymphoblastoid cells. Pathway analysis with the altered miRNAs and RNA expressions revealed differential involvement of cell communication and catalytic activity, as well as immune response signaling and NGF activation of NF-kB pathways under simulated microgravity condition. The network analysis also identified several projected networks with c- Rel, ETS1 and Ubiquitin C as key factors. In a flight experiment on the International Space Station (ISS), we will investigate the effects of actual spaceflight on miRNA expressions in nondividing human fibroblast cells in mostly G1 phase of the cell cycle. A fibroblast is a type of cell that synthesizes the extracellular matrix and collagen, the structural framework for tissues, and plays a critical role in wound healing and other functions. In addition to miRNA expressions, we will investigate the effects of spaceflight on the cellular response to DNA damages from bleomycin treatment.

Wu, Honglu↗
NASA NTRS1989

Probalistic structural analysis methods for select space propulsion system structural components

A summary of the status of this five-year project which is now in its third year of research and development is presented. The goal of the project is the development of several methodologies for probabilistic structural modeling. Probabilistic structural modeling consists of stochastic models of material properties, part geometries, boundary conditions, as well as loading conditions. The current presentation focuses on one methodology - coupling of an advanced finite element structural analysis code with probabilistic modeling strategies. The essential algorithm developments for combining the finite element and probabilistic analysis methods are reported. The validity of the resulting probabilistic structural analysis method is confirmed through a series of test problems with exact results based on Monte Carlo simulations. Additionally, the applicability of the method to a Space Propulsion System (a turbine blade) is demonstrated for static stresses.

Cruse, T. A.↗
NASA NTRS1992

Commercial turbofan engine exhaust nozzle flow analyses using PAB3D

Recent developments of a three-dimensional (PAB3D) code have paved the way for a computational investigation of complex aircraft aerodynamic components. The PAB3D code was developed for solving the simplified Reynolds Averaged Navier-Stokes equations in a three-dimensional multiblock/multizone structured mesh domain. The present analysis was applied to commercial turbofan exhaust flow systems. Solution sensitivity to grid density is presented. Laminar flow solutions were developed for all grids and two-equation k-epsilon solutions were developed for selected grids. Static pressure distributions, mass flow and thrust quantities were calculated for on-design engine operating conditions. Good agreement between predicted surface static pressures and experimental data was observed at different locations. Mass flow was predicted within 0.2 percent of experimental data. Thrust forces were typically within 0.4 percent of experimental data.

Abdol-Hamid, Khaled S.↗
NASA NTRS1994

LSENS: A General Chemical Kinetics and Sensitivity Analysis Code for homogeneous gas-phase reactions. Part 3: Illustrative test problems

LSENS, the Lewis General Chemical Kinetics and Sensitivity Analysis Code, has been developed for solving complex, homogeneous, gas-phase chemical kinetics problems and contains sensitivity analysis for a variety of problems, including nonisothermal situations. This report is part 3 of a series of three reference publications that describe LSENS, provide a detailed guide to its usage, and present many example problems. Part 3 explains the kinetics and kinetics-plus-sensitivity analysis problems supplied with LSENS and presents sample results. These problems illustrate the various capabilities of, and reaction models that can be solved by, the code and may provide a convenient starting point for the user to construct the problem data file required to execute LSENS. LSENS is a flexible, convenient, accurate, and efficient solver for chemical reaction problems such as static system; steady, one-dimensional, inviscid flow; reaction behind incident shock wave, including boundary layer correction; and perfectly stirred (highly backmixed) reactor. In addition, the chemical equilibrium state can be computed for the following assigned states: temperature and pressure, enthalpy and pressure, temperature and volume, and internal energy and volume. For static problems the code computes the sensitivity coefficients of the dependent variables and their temporal derivatives with respect to the initial values of the dependent variables and/or the three rate coefficient parameters of the chemical reactions.

Bittker, David A.↗
NASA NTRS2013

Analysis of Test Case Computations and Experiments for the First Aeroelastic Prediction Workshop

This paper compares computational and experimental data from the Aeroelastic Prediction Workshop (AePW) held in April 2012. This workshop was designed as a series of technical interchange meetings to assess the state of the art of computational methods for predicting unsteady flowfields and static and dynamic aeroelastic response. The goals are to provide an impartial forum to evaluate the effectiveness of existing computer codes and modeling techniques to simulate aeroelastic problems and to identify computational and experimental areas needing additional research and development. Three subject configurations were chosen from existing wind-tunnel data sets where there is pertinent experimental data available for comparison. Participant researchers analyzed one or more of the subject configurations, and results from all of these computations were compared at the workshop.

Schuster, David M.↗
NASA NTRS1992

Computational analysis of ramjet engine inlet interaction

A computational analysis of a ramjet engine at Mach 3.5 has been conducted and compared to results obtained experimentally. This study focuses on the behavior of the inlet both with and without combustor backpressure. Increased backpressure results in separation of the body side boundary layer and a resultant static pressure rise in the inlet throat region. The computational results compare well with the experimental data for static pressure distribution through the engine, inlet throat flow profiles, and mass capture. The computational analysis slightly underpredicts the thickness of the engine body surface boundary layer and the extent of the interaction caused by backpressure; however, the interaction is observed at approximately the same level of backpressure both experimentally and computationally. This study demonstrates the ability of two different Navier-Stokes codes, namely RPLUS and PARC, to calculate the flow features of this ramjet engine and to provide more detailed information on the process of inlet interaction and unstart.

Duncan, Beverly↗