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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Reduced-Order Modeling of Hydrogen Releases from Vent Stacks and with Wind

This report describes computational modeling in the HyRAM+ software for study of hydrogen behavior in two common scenarios. First, models of unignited plumes exiting a vent stack were considered. It was shown that entrainment and vent backpressure were major factors in plume physics. Second, HyRAM+ was extended to include wind effects on plumes by modifying the plume momentum balance and entrainment modeling. Use of the model showed that plume shape and length changed with wind speed and direction; in all cases, wind causes a shortening of the plume along the streamline. While the no-wind case in HyRAM+ has been validated and the newly developed wind model was fitted to very limited experimental data, more controlled experimental configurations would help validate the models and ensure accurate simulation of hydrogen plume behavior for vent stack releases or in wind.

08 HYDROGEN↗
NASA NTRS2005

You Can't Get There From Here! Problems and Potential Solutions in Developing New Classes of Complex Systems

The explosion of capabilities and new products within the sphere of Information Technology (IT) has fostered widespread, overly optimistic opinions regarding the industry, based on common but unjustified assumptions of quality and correctness of software. These assumptions are encouraged by software producers and vendors, who at this late date have not succeeded in finding a way to overcome the lack of an automated, mathematically sound way to develop correct systems from requirements. NASA faces this dilemma as it envisages advanced mission concepts that involve large swarms of small spacecraft that will engage cooperatively to acheve science goals. Such missions entail levels of complexity that beg for new methods for system development far beyond today's methods, which are inadequate for ensuring correct behavior of large numbers of interacting intelligent mission elements. New system development techniques recently devised through NASA-led research will offer some innovative approaches to achieving correctness in complex system development, including autonomous swarm missions that exhibit emergent behavior, as well as general software products created by the computing industry.

Hinchey, Michael G.↗
NASA NTRS1999

Evolution of Autonomous Self-Righting Behaviors for Articulated Nanorovers

Miniature rovers with articulated mobility mechanisms are being developed for planetary surface exploration on Mars and small solar system bodies. These vehicles are designed to be capable of autonomous recovery from overturning during surface operations. This paper describes a computational means of developing motion behaviors that achieve the autonomous recovery function. It proposes a control software design approach aimed at reducing the effort involved in developing self-righting behaviors. The approach is based on the integration of evolutionary computing with a dynamics simulation environment for evolving and evaluating motion behaviors. The automated behavior design approach is outlined and its underlying genetic programming infrastructure is described.

Tunstel, Edward↗
DOE OSTI2015

Development of tritium technologies at KAERI

Korea has been operating a CANDU nuclear power plant since 1983. Tritium generated in the heavy water of the plant is removed by the Wolsong TRF (Tritium Removal Facility) and measurement campaigns of tritium near the power plant have shown the efficiency of the TRF system. The HANARO reactor uses heavy water as both reflector and moderator. In HANARO the tritiated water removal system consists of compressors, condensers, and adsorption beds. A tritium behavior analysis code (TRIBAC) for a Very High Temperature Gas-Cooled Reactor (VHTR) is under development at KAERI. The TRIBAC computer software has been equipped with models for tritium production, purification, and leakage, as well as chemisorption and tritium behavior, in the hydrogen production system. Korea takes part into the ITER program and is responsible for the supply of an SDS (Tritium Storage and Delivery System). Within this program Korea has launched an experimental program to study the physico-chemical properties of metal and their hydrides in which hydrogen isotope gases can be stored and removed safely.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1994

Maximizing Performance Of A Telerobot With Minimal Software

Control software system of seven-degree-of-freedom telerobot designed to elicit maximum performance from minimal, fixed-software computer at remote robot site. Includes multiple control modules, each providing parameter-driven control of specified aspect of behavior of telerobot. Software system runs in Ada language on multiple 68020 processors or potentially on single central processing unit. Conceived for use in outer space, also proves useful in underwater construction and inspection, handling of materials in nuclear facilities, and cleaning up hazardous materials.

Backes, Paul G.↗
NASA NTRS1983

Assessment of current state of the art in modeling techniques and analysis methods for large space structures

Advances in continuum modeling, progress in reduction methods, and analysis and modeling needs for large space structures are covered with specific attention given to repetitive lattice trusses. As far as continuum modeling is concerned, an effective and verified analysis capability exists for linear thermoelastic stress, birfurcation buckling, and free vibration problems of repetitive lattices. However, application of continuum modeling to nonlinear analysis needs more development. Reduction methods are very effective for bifurcation buckling and static (steady-state) nonlinear analysis. However, more work is needed to realize their full potential for nonlinear dynamic and time-dependent problems. As far as analysis and modeling needs are concerned, three areas are identified: loads determination, modeling and nonclassical behavior characteristics, and computational algorithms. The impact of new advances in computer hardware, software, integrated analysis, CAD/CAM stems, and materials technology is also discussed.

Noor, A. K.↗
NASA NTRS2007

Adaptive Modeling of the International Space Station Electrical Power System

Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

Thomas, Justin Ray↗
DOE OSTI2017

Quantum Accelerators for High-performance Computing Systems

We define some of the programming and system-level challenges facing the application of quantum processing to high-performance computing. Alongside barriers to physical integration, prominent differences in the execution of quantum and conventional programs challenges the intersection of these computational models. Following a brief overview of the state of the art, we discuss recent advances in programming and execution models for hybrid quantum-classical computing. We discuss a novel quantum-accelerator framework that uses specialized kernels to offload select workloads while integrating with existing computing infrastructure. We elaborate on the role of the host operating system to manage these unique accelerator resources, the prospects for deploying quantum modules, and the requirements placed on the language hierarchy connecting these different system components. We draw on recent advances in the modeling and simulation of quantum computing systems with the development of architectures for hybrid high-performance computing systems and the realization of software stacks for controlling quantum devices. Finally, we present simulation results that describe the expected system-level behavior of high-performance computing systems composed from compute nodes with quantum processing units. We describe performance for these hybrid systems in terms of time-to-solution, accuracy, and energy consumption, and we use simple application examples to estimate the performance advantage of quantum acceleration.

Humble, Travis↗
NASA NTRS1993

Current capabilities for simulating the extreme distortion of thin structures subjected to severe impacts

The explicit transient dynamics technology in use today for simulating the impact and subsequent transient dynamic response of a structure has its origins in the 'hydrocodes' dating back to the late 1940's. The growth in capability in explicit transient dynamics technology parallels the growth in speed and size of digital computers. Computer software for simulating the explicit transient dynamic response of a structure is characterized by algorithms that use a large number of small steps. In explicit transient dynamics software there is a significant emphasis on speed and simplicity. The finite element technology used to generate the spatial discretization of a structure is based on a compromise between completeness of the representation for the physical processes modelled and speed in execution. That is, since it is expected in every calculation that the deformation will be finite and the material will be strained beyond the elastic range, the geometry and the associated gradient operators must be reconstructed, as well as complex stress-strain models evaluated at every time step. As a result, finite elements derived for explicit transient dynamics software use the simplest and barest constructions possible for computational efficiency while retaining an essential representation of the physical behavior. The best example of this technology is the four-node bending quadrilateral derived by Belytschko, Lin and Tsay. Today, the speed, memory capacity and availability of computer hardware allows a number of the previously used algorithms to be 'improved.' That is, it is possible with today's computing hardware to modify many of the standard algorithms to improve their representation of the physical process at the expense of added complexity and computational effort. The purpose is to review a number of these algorithms and identify the improvements possible. In many instances, both the older, faster version of the algorithm and the improved and somewhat slower version of the algorithm are found implemented together in software. Specifically, the following seven algorithmic items are examined: the invariant time derivatives of stress used in material models expressed in rate form; incremental objectivity and strain used in the numerical integration of the material models; the use of one-point element integration versus mean quadrature; shell elements used to represent the behavior of thin structural components; beam elements based on stress-resultant plasticity versus cross-section integration; the fidelity of elastic-plastic material models in their representation of ductile metals; and the use of Courant subcycling to reduce computational effort.

Key, Samuel W.↗
NASA NTRS1991

SEDS1 mission software verification using a signal simulator

The first flight of the Small Expendable Deployer System (SEDS1) is scheduled as the secondary payload of a Delta II in late 1992. The objective of the SEDS1 mission is to collect data to validate the concept of tethered satellite systems and to verify computer simulations used to predict their behavior. A series of tests will be performed to exercise the software modules which make up the Mission Software of the SEDS Data System. These tests will be performed by using a SEDS Signal Simulator to generate signals which will simulate the inputs normally produced by sensors and circuits in the SEDS system. The SEDS Signal Simulator will be used in the debugging and in the formal verification of the SEDS1 Mission Software. The Simulator will not only emulate normal flight conditions but also exercise all modules written to handle anticipated anomalous flight conditions, conditions that would be difficult to reproduce and control with actual SEDS hardware. The simulator will help to expedite software development and to increase the confidence of the users of the Mission Software. With little modification, the Simulator should be useful in the software development of future SEDS flights.

Pierson, William E.↗
NASA NTRS2015

A Flexible and Non-instrusive Approach for Computing Complex Structural Coverage Metrics

Software analysis tools and techniques often leverage structural code coverage information to reason about the dynamic behavior of software. Existing techniques instrument the code with the required structural obligations and then monitor the execution of the compiled code to report coverage. Instrumentation based approaches often incur considerable runtime overhead for complex structural coverage metrics such as Modified Condition/Decision (MC/DC). Code instrumentation, in general, has to be approached with great care to ensure it does not modify the behavior of the original code. Furthermore, instrumented code cannot be used in conjunction with other analyses that reason about the structure and semantics of the code under test. In this work, we introduce a non-intrusive preprocessing approach for computing structural coverage information. It uses a static partial evaluation of the decisions in the source code and a source-to-bytecode mapping to generate the information necessary to efficiently track structural coverage metrics during execution. Our technique is flexible; the results of the preprocessing can be used by a variety of coverage-driven software analysis tasks, including automated analyses that are not possible for instrumented code. Experimental results in the context of symbolic execution show the efficiency and flexibility of our nonintrusive approach for computing code coverage information

DO-178C↗
NASA NTRS2003

Photonic Interrogation and Control of Nano Processes

My research activities for the summer of 2003 consisted of two projects: One project was concerned with determining a method for predicting the static and dynamic assembly properties of nano-structures using laser tweezers. The other project was to investigate the generation of Laguerre-Gaussian modes using a spatial light modulator incorporated into an optical tweezers system. Concerning the first project, I initially pursued the approach suggested by my NASA colleague Dr. Art Decker. This approach involved mimicking the model of the structure of atomic nucleus for the assembly of 1 to 100 atoms using allowed quadruple transitions induced by orbital angular momentums of a Laguerre- Gaussian (Doughnut) laser mode. After realizing the inaptness of the nuclear model with the nanostructure model as far as the binding forces and transitions were concerned, I focused on using quantum dot modei. This model was not attuned also for the host lattice influences the electronic structure of the quantum dot. Thus one other option that I decided to pursue was the approach of molecular quantum mechanics. In this approach the nanostructure is treated as a large (10-100 nm) molecule constructed from single element or multi-elements. Subsequent to consultation with Dr. Fred Morales, a chemical engineer at NASA GRC, and Dr. David Ball, a computational chemist at Cleveland State University, I acquired a molecular-quantum computation software, Hyperchem 7.0. This software allows simulation of different molecular structures as far as their static and dynamic behaviors are concerned. The time that I spent on this project was about eight weeks. Once this suitable approach was identified, I realized the need to collaborate with a computational quantum chemist to pursue searching for stable nanostructures in the range of 10-100 nm that we can be assembled using laser tweezers. The second project was about generating laser tweezers that possess orbital angular momentum. As shown, we were able to generate laser tweezers modes of different orbital angular momentum using a spatial light modulator incorporated into a laser tweezers system. The motivation for investigating these types of modes stems from being able to spin particles at high speeds and also to orient two particles in separate traps and then join them together. Also, there has been recent intense interest on fundamental physics research on orbital angular momentum of light. The fact that circularly polarized light may have associated with it angular momentum that relates to the spin of individual photons (spin 0 for the plane polarized light, spin +1 for the right-circularly polarized light and spin -1 for the left-circularly polarized light) was first demonstrated by Beth in 1936. Orbital angular momentum is, however, distinct from spin in that the spin angular momentum of light is intrinsically linked to the behavior of the electric field in the light whereas orbital angular momentum is a consequence of inclined wavefronts. In 1992 L. Allen, et al showed that the Laguerre-Gaussian (LG) modes could possess well-defined orbital angular momentum that can exceed 1 planck's constant, i.e. l plancks constant per photon, where l is the azimuthal index of the mode.

Jassemnejad, Baha↗
NASA NTRS1991

Programs For Modeling Fault-Tolerant Computing Systems

Pade Approximation with Scaling, (PAWS) and Scaling Taylor Exponential Matrix (STEM) computer programs are software tools for design and validation. Provide flexible, user-friendly, language-based interface for input of Markov mathematical methods describing behaviors of fault-tolerant computer systems. Markov models include both recovery from faults via reconfiguration and behaviors of such systems when faults occur. PAWS and STEM produce exact solutions of probability of system failure and provide conservative estimate of number of significant digits in solution. Written in PASCAL and FORTRAN.

Butler, Ricky W.↗
DOE OSTI2020

Cutting the Deployment Costs of Physics-Based MPC in Buildings by Simulation-Based Imitation Learning

It has been shown that model predictive control (MPC) is a promising solution for energy-efficient building operations. However, the deployment of MPC in a large portion of the building stock has not been possible partially because of high installation costs. Every building is unique and requires a tailored MPC solution. The best performing solutions are often based on physics-based modeling, which is, however, computationally expensive and requires dedicated software. A promising direction that tackles this problem is to train a neural network-based optimal control policy to imitate the behavior of physics-based MPC from the simulation data generated offline. The neural networks give control actions that closely approximate those produced by physics-based MPC, but with a fraction of the computational and memory requirements and without the need for licensed software. The main advantage of the proposed approach stems from simple evaluation at execution time, leading to low computational footprints and easy deployment on embedded HW platforms. In the case study, we present the energy savings potential of physics-based MPC applied to an office building in Belgium. We demonstrate how neural network approximators can be used to cut the implementation and maintenance costs of MPC deployment without compromising performance. We also critically assess the presented approach by pointing out the remaining challenges and open research questions.

Drgona, Jan↗
DOE OSTI2026

Cooperative Education

Los Alamos National Laboratory (LANL) is a multidisciplinary national laboratory that conducts research and development in national security, engineering, materials science, computational modeling, and advanced manufacturing. The laboratory develops innovative technologies to address complex scientific and engineering challenges. This project focuses on the development and evaluation of high-performance absorbing structures through computational design, simulation, and engineering analysis. Absorbing structures are used in applications where damage mitigation, structural protection, and material efficiency are critical performance requirements. The increasing demand for lightweight, high-strength, and highly efficient structural systems has created a need for improved design methodologies capable of maximizing absorption while minimizing weight and material usage. The project utilizes advanced engineering software, including 3D CAD software and FEA, to generate and optimize structural concepts. Computational simulations are performed to evaluate structural behavior under loading conditions, while mathematical analyses are conducted using Python-based tools as well as established analytical equations from material and structural mechanics. The project benefits LANL by supporting the development of advanced design methodologies and improving the understanding of material and structural performance. During the internship term, a significant portion of the design development, simulation, and data analysis activities will be completed. Success of the project depends on collaboration among engineering mentors and technical staff members. Work will be conducted at Los Alamos National Laboratory using laboratory computing resources and engineering software.

42 ENGINEERING↗
DOE OSTI2020

Multiphysics for nuclear energy applications using a cohesive computational framework

With the recent development of advanced numerical algorithms, software design, and low-cost high-performance computer hardware, reliance on coupled multiphysics to predict the behavior of complex physical systems is beginning to become standard practice. This is especially true in nuclear energy applications where strong nonlinear interdependencies exist between reactor physics, radiation transport, multi-scale nuclear fuels performance, thermal fluids, etc. Resolving these nonlinear dependencies requires choices in multiphysics software approaches. Two main multiphysics modeling and simulation approaches have emerged. The first is based upon "code coupling" where disparate physics codes of different software design, code languages, and spatial and temporal integration schemes are coupled together with relatively complex data passing interfaces. The second multiphysics software approach is to employ a "cohesive" framework where all physics applications are developed with a common software design, i.e., data structures, syntax, input format, integrated spatial and temporal discretization schemes, etc. In this paper we present the Multiphysics Object-Oriented Simulation Environment (MOOSE) development and runtime framework and describe the framework's cohesive modeling and simulation multiphysics approach. Then, a "cohesive-like" extension of the MOOSE framework is presented where MOOSE-based physics software applications are efficiently coupled to non-MOOSE (external) physics codes to form multiphysics applications using MOOSE's unique interface capabilities. Finally, several examples of MOOSE's cohesive and cohesive-like multiphysics applications will be demonstrated. These multiphysics demonstrations will incorporate both MOOSE-based applications and external codes, including Nek5000, RELAP-7, TRACE, BISON, and Pronghorn.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2019

Application of Machine Learning Techniques to Aviation Operations: Promises and Challenges

There is an increasing interest in applying methods based on Machine Learning Techniques (MLT) to problems in aviation operations. The current interest is based on developments in Cloud Computing, the availability of open software and the success of MLT in automation, consumer behavior and finance involving large database. This paper reviews the current-state-of-the art in applying MLT to aviation operations, its promises and challenges. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. This paper compares the methodology used in and issues to be addressed in applying either model-driven or data-driven methods. Some aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and a rich historical database are prime candidates for data-driven methods. The application of MLT to aviation operations falls into three categories: (a) based on the lack of a physics-based model, MLT is the favored approach, (b) marginal difference between regression methods using physics-based models and MLT and (c) better results using a blend of physics-based methods combined with MLT. As always, the best approach depends on the task, the physical understanding of the problem and the quality and quantity of the available data.

Sridhar, Banavar↗
NASA NTRS2020

Observations on the Application of Machine Learning Techniques to Aviation Operations

There is an increasing interest in applying methods based on Machine Learning Techniques (MLT) to problems in aviation operations. The current interest is based on developments in Cloud Computing, the availability of open software and the success of MLT in automation, consumer behavior and finance involving large database. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. This talk describes issues to be addressed in applying either model-driven or data-driven methods. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and a rich historical database are prime candidates for analysis using data-driven methods. The issues are illustrated by a detailed example and summary of current research in the area. The application of MLT to aviation operations falls into two categories: (a) based on the lack of a physics-based model, MLT is the favored approach and (b) marginal difference between regression methods using physics-based models and MLT. Further research is needed in the selection of MLT to critical aviation operations. As always, the best approach depends on the task, the physical understanding of the problem and the quality and quantity of the available data.

Sridhar, Banavar↗