SEARCH · Engineering Papers

Results for “Large Language Models”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27

All sources NASA NTRS DOE OSTI

NASA NTRS1988

A modernized PDL approach for Ada software development

The desire to integrate newly available, graphically-oriented Computed Aided Software Engineering (CASE) tools with existing software design approaches is changing the way Program Design Language (PDL) or Process Description Language is used for large system development. In the approach documented here, Software Engineers use graphics tools to model the problem and to describe high level software design in diagrams. An Ada-based PDL is used to document low level design. Some results are provided along with an analysis for each of three smaller General Electric (GE) Ada development projects that utilized variations on this approach. Finally some considerations are identified for larger scale implementation.

Usavage, Paul, Jr.↗

NASA NTRS2004

Control System Architectures, Technologies and Concepts for Near Term and Future Human Exploration of Space

Technologies that facilitate the design and control of complex, hybrid, and resource-constrained systems are examined. This paper focuses on design methodologies, and system architectures, not on specific control methods that may be applied to life support subsystems. Honeywell and Boeing have estimated that 60-80Y0 of the effort in developing complex control systems is software development, and only 20-40% is control system development. It has also been shown that large software projects have failure rates of as high as 50-65%. Concepts discussed include the Unified Modeling Language (UML) and design patterns with the goal of creating a self-improving, self-documenting system design process. Successful architectures for control must not only facilitate hardware to software integration, but must also reconcile continuously changing software with much less frequently changing hardware. These architectures rely on software modules or components to facilitate change. Architecting such systems for change leverages the interfaces between these modules or components.

Boulanger, Richard↗

NASA NTRS2012

A Novel Technique for Running the NASA Legacy Code LAPIN Synchronously With Simulations Developed Using Simulink

This report presents a method for running a dynamic legacy inlet simulation in concert with another dynamic simulation that uses a graphical interface. The legacy code, NASA's LArge Perturbation INlet (LAPIN) model, was coded using the FORTRAN 77 (The Portland Group, Lake Oswego, OR) programming language to run in a command shell similar to other applications that used the Microsoft Disk Operating System (MS-DOS) (Microsoft Corporation, Redmond, WA). Simulink (MathWorks, Natick, MA) is a dynamic simulation that runs on a modern graphical operating system. The product of this work has both simulations, LAPIN and Simulink, running synchronously on the same computer with periodic data exchanges. Implementing the method described in this paper avoided extensive changes to the legacy code and preserved its basic operating procedure. This paper presents a novel method that promotes inter-task data communication between the synchronously running processes.

Vrnak, Daniel R.↗

NASA NTRS2013

Analyses Made to Order: Using Transformation to Rapidly Configure a Multidisciplinary Environment

Aerospace problems are highly multidisciplinary. Four or more major disciplines are involved in analyzing any particular vehicle. Moreover, the choice of implementation technology of various subsystems can lead to a change of leading domain or reformation of the driving equations. An excellent example is the change of expertise required to consider aircraft built from composite or metallic structures, or those propelled by chemical or electrical thrusters. Another example is in the major reconfiguration of handling and stability equations with different control surface configuration (e.g., canards, t-tail v four-post tail). Combinatorial problems are also commonplace anytime that a major system is to be designed. If there are only 5 attributes of a design to consider with 4 different options, this is already 1024 options. Adding just 5 more dimensions to the study explodes the space to over one million. Even generous assumptions like the idea that only 10% of the combinations are physically feasible can only contain the problem for so long. To make matters worse, the simple number of combinations is only the beginning. Combining the issue of trade space size with the need to reformulate the design problem for many of the possibilities makes life exponentially more difficult. Advances in software modeling approaches have led to the development of model-driven architecture. This approach uses the transformation of models into inferred models (e.g. inferred execution traces from state machines) or the skeletons for code generation. When the emphasis on transformation is applied to aerospace, it becomes possible to exploit redundancy in the information specified in multiple domain models into a unified system model. F1urther, it becomes possible to overcome the combinatorial nature of specifying integrated system behavior by manually combining the equations governing a given component technology. Transformations from a system specification combined with a system-analysis mapping specification enable one-click combination of domain analyses. This is a flexibility that has been missing from many engineering codes, which often entangle design specification and physical examination much more than is required to conduct the analysis. This capability has been investigated and cultivated within the DARPA F6 program by a team of JPL and Phoenix Integration engineers building the Adapatable Systems Design and Analysis (ASDA) framework. By embracing system modeling with SysML and the Query-View-Transformation (QVT) language, the ASDA team has been able to build a flexible, easily reconfigurable framework for building up and solving large tradespaces. Examples of application and lessons learned in building the framework will be described in this paper. In addition, the motivation will be laid for various tool vendors to develop open model description standards while being able to maintain competitive advantage through proprietary algorithms and approaches. These standards will also be compared to the underpinnings of model-driven architecture and the OMG standards of the Meta-Object Facility (MOF), SysML, and QVT.

Cole, Bjorn↗

NASA NTRS1995

Introduction to Penelope

A formal program verification is a (mathematical) proof that a program executed according to its intended model meets some specification. This proves that the algorithm defined by the program is correct in the precise technical sense of being consistent with a particular specification. A program correct in this sense is free from a large and important class of errors, even though its behavior may still produce unintended results--either because the implementation of the programming language itself does not match the model of execution, or because the specification does not correctly express the user's intentions. Penelope is a prototype system for interactively developing and verifying programs that are written in a rich subset of sequential Ada. Penelope can be used to develop a program and its correctness proof incrementally, and in concert with one another. Incrementality is used in a number of ways to help make verification more tractable and more productive. For example, if an already-verified program is modified, one can attempt to prove the modified version by replaying and modifying the original verification. Penelope's specification language, Larch/Ada, belongs to the family of Larch interface languages. Larch/Ada scales up properly, in the sense that it is demonstrably sound to decompose a system hierarchically and reason locally about the implementation of each piece. Penelope has been applied in various demonstration projects--for specification (guidance control, distributed operating systems), verification (of off-the-shelf code), and formal development (by non-expert as well as expert users). Some features of Penelope have been embodied in Ada Wise, a lint-like non-interactive tool that warns of the potential for certain dynamic semantic errors in Ada programs.

Guaspari, David↗

DOE OSTI2021

Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery

Machine learning (ML)-accelerated discovery requires large amounts of high-fidelity data to reveal predictive structure–property relationships. For many properties of interest in materials discovery, the challenging nature and high cost of data generation has resulted in a data landscape that is both scarcely populated and of dubious quality. Data-driven techniques starting to overcome these limitations include the use of consensus across functionals in density functional theory, the development of new functionals or accelerated electronic structure theories, and the detection of where computationally demanding methods are most necessary. When properties cannot be reliably simulated, large experimental data sets can be used to train ML models. In the absence of manual curation, increasingly sophisticated natural language processing and automated image analysis are making it possible to learn structure–property relationships from the literature. Finally, models trained on these data sets will improve as they incorporate community feedback.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Testing of Strategies for the Acceleration of the Cost Optimization

The general problem addressed in the Nuclear-Renewable Hybrid Energy System (N-R HES) project is finding the optimum economical dispatch (ED) and capacity planning solutions for the hybrid energy systems. In the present test-problem configuration, the N-R HES unit is composed of three electrical power-generating components, i.e. the Balance of Plant (BOP), the Secondary Energy Source (SES), and the Energy Storage (ES). In addition, there is an Industrial Process (IP), which is devoted to hydrogen generation. At this preliminary stage, the goal is to find the power outputs of each one of the N-R HES unit components (BOP, SES, ES) and the IP hydrogen production level that maximizes the unit profit by simultaneously satisfying individual component operational constraints. The optimization problem is meant to be solved in the Risk Analysis Virtual Environment (RAVEN) framework. The dynamic response of the N-R HES unit components is simulated by using dedicated object-oriented models written in the Modelica modeling language. Though this code coupling provides for very accurate predictions, the ensuing optimization problem is characterized by a very large number of solution variables. To ease the computational burden and to improve the path to a converged solution, a method to better estimate the initial guess for the optimization problem solution was developed. The proposed approach led to the definition of a suitable Monte Carlo-based optimization algorithm (called the preconditioner), which provides an initial guess for the optimal N-R HES power dispatch and the optimal installed capacity for each one of the unit components. The preconditioner samples a set of stochastic power scenarios for each one of the N-R HES unit components, and then for each of them the corresponding value of a suitably defined cost function is evaluated. After having simulated a sufficient number of power histories, the configuration which ensures the highest profit is selected as the optimal one. The component physical dynamics are represented through suitable ramp constraints, which considerably simplify the numerical solving. In order to test the capabilities of the proposed approach, in the present report, the dispatch problem only is tackled, i.e. a reference unit configuration is assumed, and each one of the N-R HES unit components is assumed to have a fixed installed capacity. As for the next steps, the main improvement will concern the operation strategy of the ES facility. In particular, in order to describe a more realistic battery commitment strategy, the ES operation will be regulated according to the electricity price forecasts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2013

Implementation of a Goal-Based Systems Engineering Process Using the Systems Modeling Language (SysML)

Building upon the purpose, theoretical approach, and use of a Goal-Function Tree (GFT) being presented by Dr. Stephen B. Johnson, described in a related Infotech 2013 ISHM abstract titled "Goal-Function Tree Modeling for Systems Engineering and Fault Management", this paper will describe the core framework used to implement the GFTbased systems engineering process using the Systems Modeling Language (SysML). These two papers are ideally accepted and presented together in the same Infotech session. Statement of problem: SysML, as a tool, is currently not capable of implementing the theoretical approach described within the "Goal-Function Tree Modeling for Systems Engineering and Fault Management" paper cited above. More generally, SysML's current capabilities to model functional decompositions in the rigorous manner required in the GFT approach are limited. The GFT is a new Model-Based Systems Engineering (MBSE) approach to the development of goals and requirements, functions, and its linkage to design. As a growing standard for systems engineering, it is important to develop methods to implement GFT in SysML. Proposed Method of Solution: Many of the central concepts of the SysML language are needed to implement a GFT for large complex systems. In the implementation of those central concepts, the following will be described in detail: changes to the nominal SysML process, model view definitions and examples, diagram definitions and examples, and detailed SysML construct and stereotype definitions.

Patterson, Jonathan D.↗

NASA NTRS2013

Implementation of a Goal-Based Systems Engineering Process Using the Systems Modeling Language (SysML)

Breckenridge, Jonathan T.↗

NASA NTRS1990

AiGERM: A logic programming front end for GERM

AiGerm (Artificially Intelligent Graphical Entity Relation Modeler) is a relational data base query and programming language front end for MCC (Mission Control Center)/STP's (Space Test Program) Germ (Graphical Entity Relational Modeling) system. It is intended as an add-on component of the Germ system to be used for navigating very large networks of information. It can also function as an expert system shell for prototyping knowledge-based systems. AiGerm provides an interface between the programming language and Germ.

Hashim, Safaa H.↗

DOE OSTI2023

Neural Architecture Search Benchmarks: Insights and Survey

Neural Architecture Search (NAS), a promising and fast-moving research field, aims to automate the architectural design of Deep Neural Networks (DNNs) to achieve better performance on the given task and dataset. NAS methods have been very successful in discovering efficient models for various Computer Vision, Natural Language Processing, etc. The major obstacles to the advancement of NAS techniques are the demand for large computation resources and fair evaluation of various search methods. The differences in training pipeline and setting make it challenging to compare the efficiency of two NAS algorithms. A large number of NAS Benchmarks to simulate the architecture evaluation in seconds have been released over the last few years to ease the computation burden of training neural networks and can aid in the unbiased assessment of different search methods. This paper provides an extensive review of several publicly available NAS Benchmarks in the literature. We provide technical details and a deeper understanding of each benchmark and point out future directions.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1992

Program Simulates Spacecraft Missions

IMP is simulation language used to mathematically model spacecraft missions around Earth, Moon, Mars, or other planets. Simulated missions controlled by user through selection from large menu of events and maneuvers. As many as three simulated spacecraft used; main, target, and observer. Simulation begins at lift-off or in suborbital or orbital phases. Written in FORTRAN 77.

Dauro, V. A.↗

DOE OSTI2023

Natural Language Processing-Enhanced Nuclear Industry Operating Experience Data Analysis: Aggregation and Interpretation of Multi-Report Analysis Results

Industry-wide operating experience is a critical source of raw data for reliability and risk model parameter estimations for nuclear power plants. A large portion of operating experience data are failure events stored as reports that contain unstructured data, such as narratives. In current practice, a failure report is usually reviewed and manually coded by analysts. The coding is based on extracting several event characteristics such as system name, component type, sub-part type, failure mode, and failure cause. Event narratives are mostly used to help understand events and extract their characteristics. In this line of research, we aim to maximize the usage of event narratives by leveraging natural language processing (NLP) methods to automatically convert an event narrative to a causal graph. This research has promise to improve physical understanding of failure initiation and propagation and to facilitate use of non-failure data (e.g., near-misses and degradations) to complement the limited data pool of failures. In our previous work, we developed an NLP tool and applied it to analyze a number of licensee event reports submitted by U.S. nuclear power plants to the Nuclear Regulatory Commission. In this paper, we will report our recent research progress in aggregating the results of multiple reports, developing network model(s), and drawing statistical insights.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

An autonomous laboratory for the accelerated synthesis of novel materials

To close the gap between the rates of computational screening and experimental realization of novel materials, we introduce the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the outcomes of experiments performed using robotics. Over 17 days of continuous operation, the A-Lab realized 41 novel compounds from a set of 58 targets including a variety of oxides and phosphates that were identified using large-scale ab initio phase-stability data from the Materials Project and Google DeepMind. Synthesis recipes were proposed by natural-language models trained on the literature and optimized using an active-learning approach grounded in thermodynamics. Analysis of the failed syntheses provides direct and actionable suggestions to improve current techniques for materials screening and synthesis design. The high success rate demonstrates the effectiveness of artificial-intelligence-driven platforms for autonomous materials discovery and motivates further integration of computations, historical knowledge and robotics.

36 MATERIALS SCIENCE↗

DOE OSTI2019

A Semantic Search Capability for a Grid Model Repository

The operation of electric grids is becoming more challenging due to continued increases in wind and solar generation, the proliferation of decentralization generation resources, and cyber security threats. To support the needed research, new large scale realistic public grid models have been developed and placed in a repository for access by researchers. To assist researchers in easily finding grid models that are suitable for their specific research needs, an approach to searching numerous large grid models was evaluated, prototyped and developed. Here, the research identified multiple possible approaches to using graph database techniques and a natural language processing for the search algorithm. Results of the prototype, the final approach for production repository and the search algorithm formulation are described.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1991

IMP: A performance code

IMP (Integrated Mission Program) is a simulation language and code used to model present and future Earth, Moon, or Mars missions. The profile is user controlled through selection from a large menu of events and maneuvers. A Fehlberg 7/13 Runge-Kutta integrator with error and step size control is used to numerically integrate the differential equations of motion (DEQ) of three spacecraft, a main, a target, and an observer. Through selection, the DEQ's include guided thrust, oblate gravity, atmosphere drag, solar pressure, and Moon gravity effects. Guide parameters for thrust events and performance parameters of velocity changes (Delta-V) and propellant usage (maximum of five systems) are developed as needed. Print, plot, summary, and debug files are output.

Dauro, Vincent A., Sr.↗

NASA NTRS1990

A Space Station/Payload Pointing System simulation using TREETOPS

A rigid body model of NASA's Space Station (SS)/Payload Pointing System (PPS) was built and simulated using the multibody, large angle simulation package TREETOPS, whose name refers to the tree-topology class of structures that may be simulated. SS/PPS data from a previous feasibility study utilizing the MultiOptimal Differential Equation language was used as a test case to evaluate the built-in dynamical formulation capabilities of TREETOPS. The simulation results showed close agreement with NASA-Goddard data, demonstrating the validity of the nonlinear, large angle, multi-degree of freedom TREETOPS model.

Ram, Mohan↗

DOE OSTI2014

OpenSoC Fabric

Recent advancements in technology scaling have shown a trend towards greater integration with large-scale chips containing thousands of processors connected to memories and other I/O devices using non-trivial network topologies. Software simulation proves insufficient to study the tradeoffs in such complex systems due to slow execution time, whereas hardware RTL development is too time-consuming. We present OpenSoC Fabric, an on-chip network generation infrastructure which aims to provide a parameterizable and powerful on-chip network generator for evaluating future high performance computing architectures based on SoC technology. OpenSoC Fabric leverages a new hardware DSL, Chisel, which contains powerful abstractions provided by its base language, Scala, and generates both software (C++) and hardware (Verilog) models from a single code base. The OpenSoC Fabric2 infrastructure is modeled after existing state-of-the-art simulators, offers large and powerful collections of configuration options, and follows object-oriented design and functional programming to make functionality extension as easy as possible.

Source record↗