Results for “machine reasoning” — Page 25

DOE OSTI2021

Nuclear Power Fault Diagnostics and Preventative Maintenance Optimization

Operation and maintenance costs for nuclear power plants are very large. Reactors are starting to shut down even after their operating licenses have been extended, because they are not price competitive compared to other energy sources. The nuclear industry is witnessing early closure of nuclear power plants due to economic reasons despite excellent safety records. Therefore, it is imperative to reduce costs to prevent these early closures. This paper showcases recent research into advanced fault diagnostics techniques and preventative maintenance optimization to reduce these maintenance costs. This report focuses on the condensate and feedwater system for both pressurized and boiling water reactor systems. The computerized maintenance management system, which contains the plant’s digital record of all the corrective- and preventative-maintenance work orders, was used as a ground truth to locate potential faults and label the process data as healthy or faulty. Various feature extraction techniques were utilized to further differentiate the faults from the healthy data. Support vectors machines were used to categorize other test sets of process data as healthy or faulty through a cross validation procedure. Similar faults were not found within this system leading to preventative maintenance optimization. Unnecessary amounts of preventative maintenance lead to inflated maintenance costs. This paper summarizes the steps for preventative maintenance optimization from component health determination to recommendation for action. This optimization was completed for condensate pumps, condensate booster pumps, and the respective motors that drive them.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1995

Automated Performance Prediction of Message-Passing Parallel Programs

The increasing use of massively parallel supercomputers to solve large-scale scientific problems has generated a need for tools that can predict scalability trends of applications written for these machines. Much work has been done to create simple models that represent important characteristics of parallel programs, such as latency, network contention, and communication volume. But many of these methods still require substantial manual effort to represent an application in the model's format. The NIK toolkit described in this paper is the result of an on-going effort to automate the formation of analytic expressions of program execution time, with a minimum of programmer assistance. In this paper we demonstrate the feasibility of our approach, by extending previous work to detect and model communication patterns automatically, with and without overlapped computations. The predictions derived from these models agree, within reasonable limits, with execution times of programs measured on the Intel iPSC/860 and Paragon. Further, we demonstrate the use of MK in selecting optimal computational grain size and studying various scalability metrics.

Block, Robert J.↗

DOE OSTI2022

An experimental and modeling study on auto-ignition kinetics of ammonia/methanol mixtures at intermediate temperature and high pressure

A rapid compression machine (RCM) has been applied to measure the ignition delay times of NH 3 /CH 3 OH mixtures covering pressures of 20 and 40 bar, equivalence ratios of 0.5, 1.0 and 2.0, and temperatures between 845 and 1100 K. Here the measurements show that the NH 3 /CH 3 OH mixtures become more reactive with increasing methanol addition. Addition of merely 1% (molar basis) of CH 3 OH to NH 3 lowers the ignition temperature around 100 K at 40 bar in comparison to pure NH 3 . The ignition delay is a complex function of fuel mixture and stoichiometry. For the 1% CH 3 OH mixture, the leaner mixtures are more reactive, while the reverse trend is found for mixtures with 5%, 20% and pure CH 3 OH. Analysis of the pressure profiles shows three distinct ignition modes for NH 3/ CH 3 OH mixtures, facilitated by the pre-ignition heat release from NH 3 consumption. A detailed mechanism for ignition of NH 3 /CH 3 OH fuel blends has been developed, capable of reproducing the ignition behavior of mixtures with reasonable accuracy. A subset for amine / methanol interactions was established, with rate constants for the key reaction between NH 2 and CH 3 OH calculated from ab initio theory. A sensitivity analysis indicates that the critical reactions during the auto-ignition process vary with the CH 3 OH mole fraction in the fuel. The ammonia chemistry, namely NH 2 + NO, NH2 + NO 2 and NH 2 + HO 2 , is dominant for the mixture with 1% CH 3 OH, while the reactions related to CH 3 OH and H 2 O 2 are more important for the 20% CH 3 OH mixture. The interaction between ammonia and methanol shows a more prominent effect on auto-ignition for mixtures with 5% CH 3 OH in fuel as compared to those with 1% and 20% CH 3 OH. According to the modeling results, methanol addition is found to enrich the O/H radical pool, consuming ammonia and promoting auto-ignition through different reaction pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1993

Parallel spatial direct numerical simulations on the Intel iPSC/860 hypercube

The implementation and performance of a parallel spatial direct numerical simulation (PSDNS) approach on the Intel iPSC/860 hypercube is documented. The direct numerical simulation approach is used to compute spatially evolving disturbances associated with the laminar-to-turbulent transition in boundary-layer flows. The feasibility of using the PSDNS on the hypercube to perform transition studies is examined. The results indicate that the direct numerical simulation approach can effectively be parallelized on a distributed-memory parallel machine. By increasing the number of processors nearly ideal linear speedups are achieved with nonoptimized routines; slower than linear speedups are achieved with optimized (machine dependent library) routines. This slower than linear speedup results because the Fast Fourier Transform (FFT) routine dominates the computational cost and because the routine indicates less than ideal speedups. However with the machine-dependent routines the total computational cost decreases by a factor of 4 to 5 compared with standard FORTRAN routines. The computational cost increases linearly with spanwise wall-normal and streamwise grid refinements. The hypercube with 32 processors was estimated to require approximately twice the amount of Cray supercomputer single processor time to complete a comparable simulation; however it is estimated that a subgrid-scale model which reduces the required number of grid points and becomes a large-eddy simulation (PSLES) would reduce the computational cost and memory requirements by a factor of 10 over the PSDNS. This PSLES implementation would enable transition simulations on the hypercube at a reasonable computational cost.

Joslin, Ronald D.↗

NASA NTRSDate not supplied

Performance of a Regenerative Fuel Cell System for the Lunar Surface

Regenerative fuel cells (RFCs) are an attractive energy storage solution for lunar missions as a technology capable of providing a higher specific energy (i.e., W∙h/kg) than state-of-the-art packaged Li-ion battery systems. An RFC consists of the (1 & 2) electrochemical stacks (chemical to electrical energy conversion to supply electricity to an external load, i.e. the fuel cell reaction, and electrical to chemical energy conversion of supplied electrical power to dissociate water into hydrogen and oxygen gases, i.e. water electrolysis), (3) fluidic conditioning, (4) reactant storage, (5) avionics, (6) power management and distribution (PMAD), and (7) thermal management. NASA’s Glenn Research Center has designed, assembled, and tested a breadboard RFC sys-tem capable of operating autonomously for multiple simulated lunar day/night cycles in a laboratory environment. The system is comprised of a non-flow through proton exchange membrane (PEM) fuel cell stack and a liquid-anode feed PEM electrolyzer (EZ) stack designed to electrochemically compress the reactants at balanced pressures up to 12.4 MPa (1800 psia). The fluidic conditioning, avionics, PMAD, and thermal management sub-systems are largely comprised of commercial-off-the-shelf components for this system-level development effort. The hardware is controlled by a CubeSat space processor running an operational program based on core flight architecture that can control the RFC hardware autonomously through a state machine with fault monitoring. The testing results highlighted here were completed with the system in an open-loop configuration such that reactants generated through water electrolysis were vented while gas cylinders supplied fuel cell operation. The breadboard operated autonomously, but there were five unplanned transitions to a safe state that required a manual restart after reviewing the data, determining a root cause, and implementing a solution. Four of the transitions were caused by the thermal management subsystem and the fifth was caused by a water management control issue in the EZ sub-system. The RFC system operated for over 550 hours with the final cycle being slightly abbreviated due to reasons unrelated to system performance.

Kerrigan Cain↗

NASA NTRSDate not supplied

Performance of a Regenerative Fuel Cell System for the Lunar Surface

Regenerative fuel cells (RFCs) are an attractive energy storage solution for lunar missions as a technology capable of providing a higher specific energy (i.e., W∙h/kg) than state-of-the-art packaged Li-ion battery systems. An RFC consists of the (1 & 2) electrochemical stacks (chemical to electrical energy conversion to supply electricity to an external load, i.e. the fuel cell reaction, and electrical to chemical energy conversion of supplied electrical power to dissociate water into hydrogen and oxygen gases, i.e. water electrolysis), (3) fluidic conditioning, (4) reactant storage, (5) avionics, (6) power management and distribution (PMAD), and (7) thermal management. NASA’s Glenn Research Center has designed, assembled, and tested a breadboard RFC sys-tem capable of operating autonomously for multiple simulated lunar day/night cycles in a laboratory environment. The system is comprised of a non-flow through proton exchange membrane (PEM) fuel cell stack and a liquid-anode feed PEM electrolyzer (EZ) stack designed to electrochemically compress the reactants at balanced pressures up to 12.4 MPa (1800 psia). The fluidic conditioning, avionics, PMAD, and thermal management sub-systems are largely comprised of commercial-off-the-shelf components for this system-level development effort. The hardware is controlled by a CubeSat space processor running an operational program based on core flight architecture that can control the RFC hardware autonomously through a state machine with fault monitoring. The testing results highlighted here were completed with the system in an open-loop configuration such that reactants generated through water electrolysis were vented while gas cylinders supplied fuel cell operation. The breadboard operated autonomously, but there were five unplanned transitions to a safe state that required a manual restart after reviewing the data, determining a root cause, and implementing a solution. Four of the transitions were caused by the thermal management subsystem and the fifth was caused by a water management control issue in the EZ sub-system. The RFC system operated for over 550 hours with the final cycle being slightly abbreviated due to reasons unrelated to system performance.

Kerrigan Cain↗

DOE OSTI2023

A Data Processing Pipeline for Adversarial Socio-Technical Network Analysis

With the rapid adoption of emerging technologies, there is a need to catalog and model sociotechnical interdependencies that have been historically used to influence the operation of Critical Infrastructure networks including the impacts of mergers and acquisitions, hostile takeovers, and foreign investment. Our research intends to address this need with two primary contributions. First, we have developed a data curation and processing pipeline to generate sociotechnical networks extracted from a variety of data sources including SEC filings and infrastructure asset databases. The pipeline, implemented in Apache Airflow, extracts and normalizes the representation of entities and relations, specified within ontologies. Our intent is to provide an extensible, machine-actionable approach to quickly communicate such models, reproduce previous results, and adapt them to new, unanticipated situations. Second, networks produced by our pipeline enable the development of graph-theoretic metrics that consider the properties of network components in addition to its topology. Metadata associated with network components---whether semantic, temporal, or geospatial---affects the alignment of generated networks with assumptions underlying complexity metrics. Validation of generated networks relative to component types defined by an ontology, may allow the research community to adapt metrics to the semantics of the domains being studied. Generated networks may be processed as knowledge, dynamic, or spatial graphs and enables a variety of analyses including automated reasoning and measures of network complexity. Automated reasoning views extracted entities and relations as a knowledge graph; this enables application of inference rules that represent historically-attested adversarial business methods and applies that behavior to a specific geographic context. Measures of network complexity, including degree distribution, reachability analyses, temporal analysis, and community detection can be adapted to indicate adversarial organizational influence.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1994

Does human cognition allow Human Factors (HF) certification of advanced aircrew systems?

This paper has examined the requirements of HF specification and certification within advanced or complex aircrew systems. It suggests reasons for current inadequacies in the use of HF in the design process, giving some examples in support, and suggesting an avenue towards the improvement of the HF certification process. The importance of human cognition to the operation and performance of advanced aircrew systems has been stressed. Many of the shortfalls of advanced aircrew systems must be attributed to over automated designs that show little consideration on either the mental limits or the cognitive capabilities of the human system component. Traditional approaches to system design and HF certification are set within an over physicalistic foundation. Also, traditionally it was assumed that physicalistic system functions could be attributed to either the human or the machine on a one to one basis. Moreover, any problems associated with the parallel needs, or promoting human understanding alongside system operation and direction, were generally equated in reality by the natural flexibility and adaptability of human skills. The consideration of the human component of a complex system is seen as being primarily based on manifestations of human behavior to the almost total exclusion of any appreciation of unobservable human mental and cognitive processes. The argument of this paper is that the considered functionality of any complex human-machine system must contain functions that are purely human and purely cognitive. Human-machine system reliability ultimately depends on human reliability and dependability and, therefore, on the form and frequency of cognitive processes that have to be conducted to support system performance. The greater the demand placed by an advanced aircraft system on the human component's basic knowledge processes or cognition, rather than on skill, the more insiduous the effects the human may have on that system. This paper discusses one example of an attempt to devise an improved method of specificaiton and certification with relation to the advanced aircrew system, that of the RN Merlin helicopter. The method is realized to have limitations in practice, these mainly associated with the late production of the system specification in relation to the system development process. The need for a careful appreciation of the capabilities and support needs of human cognition within the design process of a complex man machine system has been argued, especially with relation to the concept of system functionality. Unlike the physicalistic Fitts list, a new classification of system functionality is proposed, namely: (1) equipment - system equipment related; (2) cognitive - human cognition related; and (3) associated - necessary combinatin of equipment and cognitive. This paper has not proposed a method for a fuller consideration of cognition within systems design, but has suggested the need for such a method and indicated an avenue towards its development. Finally, the HF certification of advanced aircrew systems is seen as only being possible in a qualified sense until the important functions of human cognition are considered within the system design process. (This paper contains the opinions of its authors and does not necessarily refledt the standpoint of their respective organizations).

Macleod, Iain S.↗

DOE OSTI2022

Validation of ablation model for polyethylene using pulsed x-ray and proton exposures

The surface erosion of polyethylene is interrogated using pulsed x rays at the Z Machine (Sandia National Laboratories) and with proton beams at the Gamble II generator (Naval Research Laboratory) to validate a coupled model for volumetric thermal ablation, photoionization, finite-rate decomposition, and molecular recombination of radicals. The intense radiation pulses (up to ∼1014W/m2 over tens of nanoseconds) are used to generate one-dimensional vapor flows with low ionization fractions and a simplified geometry compared to typical laser ablation, allowing for evaluation of the model under local thermal equilibrium conditions. Areal momentum carried by the ensuing uniaxial hydrodynamic shock is used to indicate the extent of ablation. The threshold fluence for ablation is found to be in close correspondence with the bulk melt transition, and reasonable agreement with the model is obtained for peak temperatures in polyethylene up to 5500 K and heating rates up to 1011K/s where thermal decomposition reactions are also active.

Moore, N. W. (ORCID:0000000272259674)↗

NASA NTRSDate not supplied

DRF: A Software Architecture for a Data Marketplace to Support Advanced Air Mobility

Advanced Air Mobility is a new aviation vision, where unmanned aerial systems will trans- port passengers and cargo across urban and rural areas. Critical to the realization of this vision is the development of a digital marketplace, which allows service providers and consumers operating in the airspace ecosystem to securely exchange data and reasoning insights. In this paper, we present the architecture of a decentralized data marketplace that connects data and reasoning service providers to vehicles and other service consumers along the cloud-to-edge continuum. We also present two example use cases to demonstrate the value of our approach.

Autonomy↗

DOE OSTI2021

Nuclear Power Fault Diagnostics and Preventative Maintenance Optimization

The nuclear industry is beginning to see reactors shut down—even after their operating licenses have been extended—because they are not economically competitive with other energy sources. These early closures happen primarily due to economic reasons, despite excellent safety records. Therefore, it is imperative to reduce costs in order to prevent these early closures. One of the contributors to these economic reasons is the large operations and maintenance costs. This paper showcases recent research on advanced fault diagnostics techniques and preventative maintenance optimization (PMO) for reducing NPP maintenance costs. Specifically, it focuses on the feedwater and condensate system (FWCS) for both pressurized- and boiling-water reactor (BWR) systems. The computerized maintenance management system (CMMS), which contains the plant’s digital record of all corrective maintenance (CM) and preventative maintenance (PM) work orders, provided the ground truth for locating potential faults and labeling the process data as either healthy or faulted. Various feature extraction techniques were used to further differentiate the faulted data from the healthy data. Through a cross-validation procedure, support vectors machines were used to label other test sets of process data as either healthy or faulted. With relatively few faults identified in the BWR system, the potential for PMO opens up, since an unnecessary amount of PM leads to inflated maintenance costs. The steps for PMO are summarized, from component health determinations to recommendations for action. An example of PMO assessment is presented for condensate pumps, condensate booster pumps, and the respective motors that drive them.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Nuclear Power Fault Diagnostics and Preventative Maintenance Optimization NPIC presentation

The nuclear industry is beginning to see reactors shut down—even after their operating licenses have been extended—because they are not economically competitive with other energy sources. These early closures happen primarily due to economic reasons, despite excellent safety records. Therefore, it is imperative to reduce costs in order to prevent these early closures. One of the contributors to these economic reasons is the large operations and maintenance costs. This paper showcases recent research on advanced fault diagnostics techniques and preventative maintenance optimization (PMO) for reducing NPP maintenance costs. Specifically, it focuses on the feedwater and condensate system (FWCS) for both pressurized- and boiling-water reactor (BWR) systems. The computerized maintenance management system (CMMS), which contains the plant’s digital record of all corrective maintenance (CM) and preventative maintenance (PM) work orders, provided the ground truth for locating potential faults and labeling the process data as either healthy or faulted. Various feature extraction techniques were used to further differentiate the faulted data from the healthy data. Through a cross-validation procedure, support vectors machines were used to label other test sets of process data as either healthy or faulted. With relatively few faults identified in the BWR system, the potential for PMO opens up, since an unnecessary amount of PM leads to inflated maintenance costs. The steps for PMO are summarized, from component health determinations to recommendations for action. An example of PMO assessment is presented for condensate pumps, condensate booster pumps, and the respective motors that drive them.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

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↗

DOE OSTI2021

Inverse Design of Plasma Metamaterial Devices for Optical Computing

We apply inverse-design methods to produce two-dimensional plasma metamaterial (PMM) devices. Backpropagated finite-difference frequency-domain (FDFD) simulations are used to design waveguides and demultiplexers operating under both TE and TM modes. Demultiplexing and waveguiding are demonstrated for devices composed of plasma elements with reasonable plasma densities of approximately 7 GHz, allowing for future in situ training and experimental realization of these designs. We also explore the possible applicability of PMMs to nonlinear boolean operations for use in optical computing. Functionally complete logical connectives (or and and) are achieved in the TM mode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

The Evolution of Volatile Memory Forensics

The collection and analysis of volatile memory is a vibrant area of research in the cybersecurity community. The ever-evolving and growing threat landscape is trending towards fileless malware, which avoids traditional detection but can be found by examining a system’s random access memory (RAM). Additionally, volatile memory analysis offers great insight into other malicious vectors. It contains fragments of encrypted files’ contents, as well as lists of running processes, imported modules, and network connections, all of which are difficult or impossible to extract from the file system. For these compelling reasons, recent research efforts have focused on the collection of memory snapshots and methods to analyze them for the presence of malware. However, to the best of our knowledge, no current reviews or surveys exist that systematize the research on both memory acquisition and analysis. We fill that gap with this novel survey by exploring the state-of-the-art tools and techniques for volatile memory acquisition and analysis for malware identification. For memory acquisition methods, we explore the trade-offs many techniques make between snapshot quality, performance overhead, and security. For memory analysis, we examined the traditional forensic methods used, including signature-based methods, dynamic methods performed in a sandbox environment, as well as machine learning-based approaches. We summarize the currently available tools, and suggest areas for more research.

Nyholm, Hannah↗

NASA NTRS1986

Description of a 20 Kilohertz power distribution system

A single phase, 440 VRMS, 20 kHz power distribution system with a regulated sinusoidal wave form is discussed. A single phase power system minimizes the wiring, sensing, and control complexities required in a multi-sourced redundantly distributed power system. The single phase addresses only the distribution link; mulitphase lower frequency inputs and outputs accommodation techniques are described. While the 440 V operating potential was initially selected for aircraft operating below 50,000 ft, this potential also appears suitable for space power systems. This voltage choice recognizes a reasonable upper limit for semiconductor ratings, yet will direct synthesis of 220 V, 3 power. A 20 kHz operating frequency was selected to be above the range of audibility, minimize the weight of reactive components, yet allow the construction of single power stages of 25 to 30 kW. The regulated sinusoidal distribution system has several advantages. With a regulated voltage, most ac/dc conversions involve rather simple transformer rectifier applications. A sinusoidal distribution system, when used in conjunction with zero crossing switching, represents a minimal source of EMI. The present state of 20 kHz power technology includes computer controls of voltage and/or frequency, low inductance cable, current limiting circuit protection, bi-directional power flow, and motor/generator operating using standard induction machines. A status update and description of each of these items and their significance is presented.

Hansen, I. G.↗

NASA NTRS1986

Description of a 20 kilohertz power distribution system

A single phase, 440 VRMS, 20 kHz power distribution system with a regulated sinusoidal wave form is discussed. A single phase power system minimizes the wiring, sensing, and control complexities required in a multi-sourced redundantly distributed power system. The single phase addresses only the distribution links multiphase lower frequency inputs and outputs accommodation techniques are described. While the 440 V operating potential was initially selected for aircraft operating below 50,000 ft, this potential also appears suitable for space power systems. This voltage choice recognizes a reasonable upper limit for semiconductor ratings, yet will direct synthesis of 220 V, 3 power. A 20 kHz operating frequency was selected to be above the range of audibility, minimize the weight of reactive components, yet allow the construction of single power stages of 25 to 30 kW. The regulated sinusoidal distribution system has several advantages. With a regulated voltage, most ac/dc conversions involve rather simple transformer rectifier applications. A sinusoidal distribution system, when used in conjunction with zero crossing switching, represents a minimal source of EMI. The present state of 20 kHz power technology includes computer controls of voltage and/or frequency, low inductance cable, current limiting circuit protection, bi-directional power flow, and motor/generator operating using standard induction machines. A status update and description of each of these items and their significance is presented.

Hansen, I. G.↗

DOE OSTI2022

The CALPHAD approach for HEAs: Challenges and opportunities

Phases are key microstructural features that determine material properties. The most intuitive way of representing phase stability in a material is by its phase diagram. The vastness of the composition space is the most compelling reason for investigating high-entropy alloys (HEAs), but it also creates major challenges in controlling phases and microstructures of HEAs due to lack of experimental phase diagrams in highly concentrated multicomponent space. The CALPHAD (Calculation of Phase Diagram) approach, although it needs improvements, is the only viable way to calculate multicomponent phase diagrams. The two major property databases in CALPHAD, Gibbs energy and mobility, when coupled, can provide not only the equilibrium phase information, but also information about diffusion and kinetics. In this article, we will review the use of the CALPHAD approach in understanding phase stability and diffusion in high-entropy alloys. Finally, we will discuss the notable trend of coupling the high-throughput CALPHAD approach with machine learning in HEA design.

36 MATERIALS SCIENCE↗