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At least 865 records · Page 48

Validation and Verification for INL Modelica-based TEDS models Via Experimental Results

This report provides an overview on the verification and validation (V&V) of the Thermal Energy Distribution System (TEDS) model developed in the Modelica process modeling ecosystem using experimental data. Model development has led to the creation of a dynamic process model of the experimental TEDS facility housed within the Energy Systems Laboratory (ESL) at Idaho National Laboratory (INL). The model was then used during the preconstruction phase of the experimental effort to inform experimental design (e.g., insulation requirements, bypass line placement, expected performance of components) and to test innovative control schemes prior to the initial operation. The TEDS model developed in Modelica includes the primary components of the TEDS experimental unit: a 200kW Chromalox heater; a single-tank packed-bed thermal energy storage system filled with 0.125-inch alumina (Al2O3) beads; an ethylene-glycol-to-Therminol-66 heat exchanger; system piping; five control valves; and all associated temperature, pressure, and volumetric flow sensors. Using the Institute of Electrical and Electronics Engineers (IEEE) V&V methodologies, considered the gold standard in the engineering field, the model was verified using a combination of static analysis, spatial convergence, and regression tests. Then using dynamic time warping (DTW) initial runs to validate and tune the TEDS model versus the experiment were conducted. This tuning method was accomplished using the INL Risk Analysis Virtual ENvironment (RAVEN) software package. Tuning is required to account for physical phenomena that are less understood within the empirical heat transfer correlations. Through the commencement of this work, a systems-level model of TEDS with associated control systems, sensors, piping diameters, and component capabilities has been created. This model was utilized in the pre-experimental phase to inform system design, insulation thicknesses, and potential control schemes to operate the system effectively and safely. Then, initial experimental startup and operational data were used to demonstrate the validation and tuning methodology. This process demonstrates the classical two-step approach of a model informing experimental design followed by the experiment validation and tuning the model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Model development for flash boiling spray and validations with isooctane, hexane, ethanol and their binary mixtures

The objective of this study is to develop a comprehensive model for spray atomization under the consideration of flash boiling, which includes nucleation, bubble growth, and droplet breakup. Although flash boiling has been previously studied, there is still no well-established analytical and numerical model of their mechanisms, or general guidelines on the implementation of this atomization strategy. In this study, detailed formulations are elaborated for the unified spray atomization model under both non-flash and flash boiling conditions. Next, the model was implemented into CFD software and 3-D simulations were performed for model validations. Two fuel blends are tested: ethanol-isooctane blends and hexane-isooctane blends. Simulation results were compared with the experimental measurements conducted using two methodologies, DBI (Diffuse Backlight Imaging) system for spray images captured by a high-speed camera, and a PDA (Phase Doppler Anemometry) system for droplet size measurement during the spray injection process. It was found that the current flash boiling model can accurately capture the spray characteristics under different environment conditions, such as the spray plume interactions and liquid penetration. The averaged Sauter mean diameter (SMD) calculations match the measurement sufficiently well. The spray structures for both single- and multi-component fuels during the injection process are well represented by current model.

42 ENGINEERING↗

AI ATAC 1: An Evaluation of Prominent Commercial Malware Detectors

This work presents an evaluation of six prominent commercial endpoint malware detectors, a network malware detector, and a file-conviction algorithm from a cyber technology vendor. The evaluation was administered as the first of the Artificial I ntelligence Applications t o Autonomous Cybersecurity (AI ATAC) prize challenges, funded by / completed in service of the US Navy. The experiment employed 100K files (50/50% benign/malicious) with a stratified distribution of file types, including ~1K zero-day program executables (increasing experiment size two orders of magnitude over previous work). We present an evaluation process of delivering a file to a fresh virtual machine donning the detection technology, waiting 90s to allow static detection, then executing the file and waiting another period for dynamic detection; this allows greater fidelity in the observational data than previous experiments, in particular, resource and time-to-detection statistics. To execute all 800K trials (100K files × 8 tools), a software framework is designed to choreograph the experiment into an automated, time-synced, and reproducible workflow with substantial parallelization. Software with base classes for this framework are provided. A cost-benefit model was configured to integrate the tools’ detection statistics into a comparable quantity by simulating costs of use. This provides a ranking methodology for cyber competitions and a lens for reasoning about the varied statistical results. The results provide insights on state of commercial malware detection.

Bridges, Robert↗

The SIFT computer and its development

Software Implemented Fault Tolerance (SIFT) is an aircraft control computer designed to allow failure probability of less than 10 to the -10th/hour. The system is based on advanced fault-tolerance computing and validation methodology. Since confirmation of reliability by observation is essentially impossible, system reliability is estimated by a Markov model. A mathematical proof is used to justify the validity of the Markov model. System design is represented by a hierarchy of abstract models, and the design proof comprises mathematical proofs that each model is, in fact, an elaboration of the next more abstract model.

Goldberg, J.↗

Impact of domain analysis on reuse methods

The SPS is performing a study for the U.S. Army CECOM on the impact of domain analysis on reuse methods. Domain analysis is the first activity that should be performed in the development of reusable software. It identifies the commonalities between systems within a given problem (such as navigation systems or database management). In the software arena these commonalities are implemented as software components that can be reused by new systems within that application domain. The objectives of the study are to develop an approach that makes domain analysis practical and effective for the Army, to reinforce the importance of domain analysis for software reuse programs, and to summarize and coalesce domain analysis information into a single reference source. Existing methods and tools are being analyzed, critical issues identified, and key automation issues addressed. Based on these, a methodology and set of guidelines for domain analysis are being developed. Potential automated tools will be identified for each activity in the methodology.

Gilroy, Kathy↗

Robotic assembly of large space structures

The Automated Structures Assembly Laboratory (ASAL) has been developed at LaRC for the following purposes: identifying the problems associated with assembling large space structures using robotic manipulators; investigating systems and techniques applicable to such assembly tasks; and developing methodology for an in-space construction facility. The ASAL facility and its robotic manipulator system is described, and a discussion of the initial series of assembly operations are included. The status of the system software development is summarized, and an outline for follow-on testing and expanded capability is given.

Will, Ralph W.↗

Risk-Based Object Oriented Testing

Software testing is a well-defined phase of the software development life cycle. Functional ("black box") testing and structural ("white box") testing are two methods of test case design commonly used by software developers. A lesser known testing method is risk-based testing, which takes into account the probability of failure of a portion of code as determined by its complexity. For object oriented programs, a methodology is proposed for identification of risk-prone classes. Risk-based testing is a highly effective testing technique that can be used to find and fix the most important problems as quickly as possible.

Rosenberg, Linda H.↗

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↗

Risk-Informed Safety Assurance and Probabilistic Assessment of Mission-Critical Software-Intensive Systems

This report validates and documents the detailed features and practical application of the framework for software intensive digital systems risk assessment and risk-informed safety assurance presented in the NASA PRA Procedures Guide for Managers and Practitioner. This framework, called herein the "Context-based Software Risk Model" (CSRM), enables the assessment of the contribution of software and software-intensive digital systems to overall system risk, in a manner which is entirely compatible and integrated with the format of a "standard" Probabilistic Risk Assessment (PRA), as currently documented and applied for NASA missions and applications. The CSRM also provides a risk-informed path and criteria for conducting organized and systematic digital system and software testing so that, within this risk-informed paradigm, the achievement of a quantitatively defined level of safety and mission success assurance may be targeted and demonstrated. The framework is based on the concept of context-dependent software risk scenarios and on the modeling of such scenarios via the use of traditional PRA techniques - i.e., event trees and fault trees - in combination with more advanced modeling devices such as the Dynamic Flowgraph Methodology (DFM) or other dynamic logic-modeling representations. The scenarios can be synthesized and quantified in a conditional logic and probabilistic formulation. The application of the CSRM method documented in this report refers to the MiniAERCam system designed and developed by the NASA Johnson Space Center.

Guarro, Sergio B.↗

NASA Tech Briefs, December 2013

Topics include: Microwave Kinetic Inductance Detector With; Selective Polarization Coupling; Flexible Microstrip Circuits for; Superconducting Electronics; CFD Extraction Tool for TecPlot From DPLR Solutions; RECOVIR Software for Identifying Viruses; Enhanced Contact Graph Routing (ECGR) MACHETE Simulation Model; Orbital Debris Engineering Model (ORDEM) v.3; Scatter-Reducing Sounding Filtration Using a Genetic Algorithm and Mean Monthly Standard Deviation; Thermo-Mechanical Methodology for Stabilizing Shape Memory Alloy Response; Hermetic Seal Designs for Sample Return Sample Tubes; Silicon Alignment Pins: An Easy Way To Realize a Wafer-to-Wafer Alignment; Positive-Buoyancy Rover for Under Ice Mobility; Electric Machine With Boosted Inductance to Stabilize Current Control; International Space Station-Based Electromagnetic Launcher for Space Science Payloads; Advanced Hybrid Spacesuit Concept Featuring Integrated Open Loop and Closed Loop Ventilation Systems; Data Quality Screening Service.

Source record↗

Workshop Report: 2021 International Symposium of Quantitative Codesign of Supercomputers

This report provides general information about the First International Symposium on the Quantitative Design of Supercomputers (SQCS). This new workshop was held in conjunction with Supercomputing ’21 on November 19, 2021, in St Louis Missouri. The symposium aims at combining two methodologies—collaborative codesign and data-driven analysis—to realize the potential of supercomputing more fully. We refer to the design solutions that rely on intelligence from data-driven insights across applications, systems, system software, workflows, and facilities as quantitative codesign of supercomputers.

Jones, Terry↗

Workshop Report: 2022 International Symposium of Quantitative Codesign of Supercomputers

This report provides general information about the Second International Symposium on the Quantitative Design of Supercomputers (SQCS). This new workshop was held in conjunction with Supercomputing ’22 on November 13, 2022, in Dallas Texas. The symposium aims at combining two methodologies—collaborative codesign and data-driven analysis—to realize the potential of supercomputing more fully. We refer to the design solutions that rely on intelligence from data-driven insights across applications, systems, system software, workflows, and facilities as quantitative codesign of supercomputers.

Jones, Terry↗

Forward Technology Solar Cell Experiment (FTSCE) for MISSE-5 Verified and Readied for Flight on STS-114

The Forward Technology Solar Cell Experiment (FTSCE) is a space solar cell experiment built as part of the Fifth Materials on the International Space Station Experiment (MISSE-5): Data Acquisition and Control Hardware and Software. It represents a collaborative effort between the NASA Glenn Research Center, the Naval Research Laboratory, and the U.S. Naval Academy. The purpose of this experiment is to place current and future solar cell technologies on orbit where they will be characterized and validated. This is in response to recent on-orbit and ground test results that raised concerns about the in-space survivability of new solar cell technologies and about current ground test methodology. The various components of the FTSCE are assembled into a passive experiment container--a 2- by 2- by 4-in. folding metal container that will be attached by an astronaut to the outer structure of the International Space Station. Data collected by the FTSCE will be relayed to the ground through a transmitter assembled by the U.S. Naval Academy. Data-acquisition electronics and software were designed to be tolerant of the thermal and radiation effects expected on orbit. The experiment has been verified and readied for flight on STS-114.

Jenkins, Phillip P.↗

A coupled fluid-mechanical workflow to simulate the directed energy deposition additive manufacturing process

Simulation of additive manufacturing processes can provide essential insight into material behavior, residual stress, and ultimately, the performance of additively manufactured parts. In this work, we describe a new simulation based workflow utilizing both solid mechanics and fluid mechanics based formulations within the finite element software package SIERRA (Sierra Solid Mechanics Team in Sierra/Solid Mechanics 4.52 User’s Guide SAND2019-2715. Technical report, Sandia National Laboratories, 2011) to enable integrated simulations of directed energy deposition (DED) additive manufacturing processes. In this methodology, a high-fidelity fluid mechanics based model of additive manufacturing is employed as the first step in a simulation workflow. This fluid model uses a level set field to track the location of the boundary between the solid material and background gas and precisely predicts temperatures and material deposition shapes from additive manufacturing process parameters. Next, the resulting deposition shape and temperature field from the fluid model are then mapped into a solid mechanics formulation to provide a more accurate surface topology for radiation and convection boundary conditions and a prescribed temperature field. Solid mechanics simulations are then conducted to predict the evolution of material stresses and microstructure within a part. By combining thermal history and deposition shape from fluid mechanics with residual stress and material property evolutions from solid mechanics, additional fidelity and precision are incorporated into additive manufacturing process simulations providing new insight into complex DED builds.

36 MATERIALS SCIENCE↗

A Thermodynamic Model Toward the Comprehension of Ferrous Burden Softening and Melting Using FactSage Macro-Processing

The softening and melting properties of iron-bearing materials play a decisive role in the formation of the cohesive zone, which greatly affects blast furnace gas flow distribution and heat-transfer efficiency. To improve the understanding regarding the evolution of condensed phases during reduction, softening, and melting, a thermodynamic model has been developed using FactSage™ thermodynamic software and macro-processing. The model was constructed using a series of equilibrium stages and splitters to determine flow directions of streams and to consider kinetic inhibitions. For all iron-bearing materials studied, the methodology proposed for modeling was capable of obtaining reduction degrees in very good agreement to its experimental data. The evolution of solid phases was qualitatively comparable to the available literature, with Fayalite, Kirschsteinite, Melilite, and FeO as the main solid phases in equilibrium before slag formation. The comparison between the profiles of the calculated slag mass fraction and the experimental pressure drop showed a close relation between these properties. Moreover, the level of heterogeneity of each raw material may play a significant role in the interpretation of its results.

36 MATERIALS SCIENCE↗

Performance-Aligned LLMs for Generating Fast HPC Code

Optimizing scientific software is a difficult task because codebases are often large and complex, and performance can depend upon several factors including the algorithm, its implementation, and hardware among others. Causes of poor performance can originate from disparate sources and be difficult to diagnose. Recent years have seen a multitude of work that use large language models (LLMs) to assist in software development tasks. However, these tools are trained to model the distribution of code as text, and are not specifically designed to understand performance aspects of code. In this work, we introduce a reinforcement learning based methodology to align the outputs of code LLMs with performance. This allows us to build upon the current code modeling capabilities of LLMs and extend them to generate better performing code. Here, we demonstrate that our fine-tuned model improves the expected speedup of generated code over base models for a set of benchmark tasks from 0.9 to 1.6 for serial code and 1.9 to 4.5 for OpenMP parallel code.

Computer science↗

Applying the ATOM drug discovery platform to small-molecule antivirals (Annual Report)

The objective of this project is to advance our understanding of the ML approaches needed to find the most potent inhibitor through an AI guided search that simultaneously optimizes for limited off-target safety activity and desirable pharmacokinetics (PK) properties. The methods will be tested for inhibiting SARS-CoV-2 activity through inhibition of the main protease as a demonstration, but the methodology will be developed to apply to any biothreat target using a small-molecule protein binding-based intervention, with limited experimental data. Computational experiments are conducted using our ATOM generative molecular design (GMD) loop software, which is the implementation of our AI/ML drug design pipeline.

59 BASIC BIOLOGICAL SCIENCES↗

Investigating Temperature Uniformity and Accuracy in PV Module Lamination: A Verification Study

This study investigates the temperature uniformity and accuracy of a photovoltaic (PV) module lamination process by addressing inconsistencies identified in 2017 data where irregular temperature changes were observed across setpoints. The 2017 data showed a notable drop in temperature upon bladder initiation, except for the 145 degrees Celsius profile. This inconsistency indicated potential inaccuracies in manual data recording methods. To address this concern, a verification experiment was conducted to evaluate temperature uniformity across the 2014 Bent River SPL2828 laminator platen and within test samples. Thermocouples, paired with Omega data acquisition software, were deployed to measure temperatures at multiple platen locations and within test samples. The experiment compared lamination temperatures of polyethylene-co-vinyl acetate (EVA) encapsulant when paired with solite glass or TPE backsheets. The methodology included verifying temperature uniformity directly on the platen and by using a large glass/EVA/glass sample using multiple thermocouples. Smaller samples were built with glass/EVA/glass and glass/EVA/backsheet configurations with one centered thermocouple to verify and compare sample temperatures. This verification aims to refine lamination temperature profiles, enhance data accuracy and provide insights into optimal process control for uniform module lamination. Ensuring consistent and uniform lamination may improve the accuracy and reliability of research outcomes.

14 SOLAR ENERGY↗