Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “primary control”

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.

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

At least 685 records · Page 38

The safety of pranlukast and montelukast during the first trimester of pregnancy: A prospective, two‐centered cohort study in Japan

Abstract For leukotriene receptor antagonists (LTRAs), especially pranlukast, safety data during pregnancy is limited. Therefore, we conducted a prospective, two‐centered cohort study using data from teratogen information services in Japan to clarify the effects of LTRA exposure during pregnancy on maternal and fetal outcomes. Pregnant women who being counseled on drug use during pregnancy at two facilities were enrolled. The primary outcome of this study was major congenital anomalies. The incidence of major congenital anomalies in women exposed to montelukast or pranlukast during the first trimester of pregnancy was compared with that of controls. Logistic regression analysis was performed to analyze the effects of maternal LTRA use during the first trimester of pregnancy on major congenital anomalies. The outcomes of 231 pregnant women exposed to LTRAs (montelukast n = 122; pranlukast n = 106; both n = 3) and 212 live births were compared with those of controls. The rate of major congenital anomalies in the LTRA group was 1.9%. Multivariable logistic regression analysis revealed that LTRA exposure was not a risk factor for major congenital anomalies (adjusted odds ratio, 0.78; 95% confidence interval, 0.23–2.05; p = 0.653). In addition, no significant difference was detected in stillbirth, spontaneous abortion, preterm birth, and low birth weight between the two groups. The present study revealed that montelukast and pranlukast were not associated with the risk of major congenital anomalies. Our findings suggest that LTRAs could be safely employed for asthma therapy during pregnancy.

Hatakeyama, Shiro↗

Experimental study of UV induced tensile properties deterioration and chemical aging of polyurea–POSS composites

Ultraviolet (UV) radiation present in natural sunlight degrades the chemical and mechanical properties of polymeric matrices in composites. Polyurea possess a unique set of chemical and mechanical properties due to its complex microstructure comprising of hard and soft segments (phases). The primary objective of the work presented here is to characterize the chemical and mechanical degradation of pure polyurea and polyurea - polyhedral oligomeric silsesquioxane (POSS) nanocomposites subjected to UV radiation exposure for 45 days. Control specimen in as-received condition (reference specimen) and UV-aged tensile test specimen are tested in the study. Analysis of Fourier transformed infrared (FTIR) spectra for UV-aged polyurea and polyurea-POSS composites reveals that the addition of POSS nanoparticles accelerate the deterioration of polyurea matrix by breaking the hard phase network and altering the mechanism of degradation for the soft phase present in polyurea microstructure. The deterioration of hard and soft segments cause a significant reduction in tensile properties of polyurea-POSS composites.

Materials Science↗

Artificial Reasoning System for Symptom-Based Conditional Failure Probability Estimation Using Bayesian Network

Advances in nuclear power technologies require enhanced capabilities for operator advice and autonomous control. One of the first tasks in the development of such capabilities is the formulation of symptom-based conditional failure probabilities for structures, systems, and components (SSCs) of interest, for which the primary goal is to aid plant personnel in deducing the probabilistic performance status of the monitored SSCs and in detecting impending faults/failure. The task of conditional failure probability estimation is a bidirectional inference problem and shall be logically tackled by the Bayesian network (BN) approach. As a knowledge-based artificial intelligence tool and a probabilistic graphical model, BN offers the capability of reasoning under uncertainty and graphical representation emulating the physical behavior of the target SSC. This paper provides a systematic overview of the BN technique and the software tools for handling implementation of BN models, along with the associated knowledge representation and reasoning paradigm. Both operational data and expert judgement can be readily incorporated into the knowledge base of a BN model. The challenges with data availability are highlighted, and the general approach to target SSC identification is presented. Our focus is upon failure-prone and risk-important balance of plant assets, especially cases having strong operator involvement. An exemplary case study on the failure of a motor-driven centrifugal pump is also conducted to demonstrate the usefulness and technical feasibility of the proposed artificial reasoning system using an expert system shell.

Zhao, Xingang↗

MRDIS Case Study

The Mobile Radiation Detection and Identification System (MRDIS) is a large mobile scanner that inspects containers in transit from cargo ships for radiological materials. The MRDIS platform operates as a two-part system with one MRDIS using a plastic Polyvinyl Toleune (synthetic polymer) for primary detection and another MRDIS that uses spectroscopic detectors for secondary isotopic identification. MRDIS can operate either independently or as part of a team, depending on the needs of the port. MRDIS is controlled by a human operator, who searches the computer monitor for any traces of radiological materials when the containers pass through the center of the system. Each MRDIS can also feed data into a central system or collect data on its own for additional material analysis. The system integrates radiation detection, radioisotope identification, an optical character recognition system, occupancy/speed sensors, wireless communications, and data processing capabilities to discern what specific radiological materials are of particular interest. In addition, Sandia engineers created a detailed set of requirements for subsequent models, allowing for faster implementation of additional detection systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are identifying hidden geothermal resources in the USA and designing profitable enhanced geothermal systems (EGS). Many non-obvious processes and parameters could characterize geothermal resources and could control the ultimate energy potential of geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize geothermal resources, but this data is sparse and multi-scale that has hindered attempts to leverage the datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) give promise to overcome these issues. Modern ML methods and tools can (1) analyze large datasets, (2) assimilate model ensembles that include a multitude of inputs and outputs, (3) process sparse datasets, (4) perform transfer learning between sites with different data quality, (5) extract hidden geothermal signatures from field and simulation data, (6) label geothermal resources and processes, (7) identify highvalue data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies.

58 GEOSCIENCES↗

Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are identifying hidden geothermal resources in the USA and designing profitable enhanced geothermal systems (EGS). Many non-obvious processes and parameters could characterize geothermal resources and could control the ultimate energy potential of geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize geothermal resources, but this data is sparse and multi-scale. This has hindered attempts to leverage the datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) give promise to overcome these issues. Modern ML methods and tools can (1) analyze large datasets, (2) assimilate model ensembles that include a multitude of inputs and outputs, (3) process sparse datasets, (4) perform transfer learning between sites with different data quality, (5) extract hidden geothermal signatures from field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. In this work, we implement ML-based geothermal exploration and an enhanced geothermal systems (EGS) design tool to achieve the above goals. Our exploration tool is GeoThermalCloud (GTC) EGS design tool is GeoDT-ML. GTC (github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. It enables the identification of critical measurements needed to identify geothermal resource signatures. GeoDT-ML (github.com/SmartTensors/GeoThermalCloud.jl/tree/master/) adds coupling to GeoDT (https://github.com/GeoDesignTool/GeoDT.git) for stochastic EGS design optimization and performance prediction. GeoDT-ML leverages recent advances in deep learning and high-performance computing. Contributors to this effort include LANL, PNNL, Google, Stanford, and Julia Computing.

15 GEOTHERMAL ENERGY↗

System and methods for deploying payloads

Embodiments of the present invention include systems for launching primary or secondary payloads or actuating other launch vehicle or payload or instrumentation devices. The system includes an adapter assembly and at least one sequencer mounted to the adapter assembly. The sequencer includes: controller boards, each of the controller boards having a controller for controlling deployment of the payloads and data files; output ports coupled to the controller boards and configured to transmit signals from the controller boards to dispensers therethrough, deployment mechanisms containing the payloads, the adapter assembly having channels for accommodating the dispensers; and a detector coupled to the controller boards and adapted to detect an external signal and, in response to the external signal, to send an initiation signal to the controller boards. The system also includes at least one power supply coupled to the sequencer and adapted to provide an electrical power to the sequencer.

42 ENGINEERING↗

Advanced Reactor Cyber Analysis and Development Environment (ARCADE) for System-Level Design Analysis

Cybersecurity is a persistent concern to the safety and security of Nuclear Power Plants (NPPs), but has lacked data-driven, evidence-based research. Rigorous cybersecurity analysis is critical for the licensing of advanced reactors using a performance-based approach. One tool that enables cybersecurity analysis is modeling and simulation. The nuclear industry makes extensive use of modeling and simulation throughout the decision process but lacks a method to incorporate cybersecurity analysis with existing models. To meet this need, the Advanced Reactor Cyber Analysis and Development Environment (ARCADE) was developed. ARCADE is a suite of publicly available tools that can be used to develop emulations of industrial control system devices and networks and integrate those emulations with physics simulators. This integration of cyber emulations and physics models enables rigorous cyber-physical analysis of cyber-attacks on NPP systems. This report provides an overview of key considerations for using ARCADE with existing physics models and demonstrates ARCADE’s capabilities for cybersecurity analysis. Using a model of the Small Modular Advanced High Temperature Reactor (SmAHTR), ARCADE was able to determine the sensitivity of the primary heat exchangers (PHX) to coordinated cyber-attacks. The analysis determined that while the PHX’s failures cause disruption to the reactor, they did not cause any safety limits to be exceeded because of the plant design, including passive safety features. Further development of ARCADE will enable rigorous, repeatable, and automated cyber-physical analysis of advanced reactor control systems. These efforts will also help reduce regulatory uncertainty by presenting similar types of cybersecurity analyses in a common format, driving standard approaches and reporting.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

An Enzymatic Platform for Primary Amination of 1-Aryl-2-alkyl Alkynes

Propargyl amines are versatile synthetic intermediates with numerous applications in the pharmaceutical industry. An attractive strategy for efficient preparation of these compounds is nitrene propargylic C(sp 3 )–H insertion. However, achieving this reaction with good chemo-, regio-, and enantioselective control has proven to be challenging. Here, we report an enzymatic platform for the enantioselective propargylic amination of alkynes using a hydroxylamine derivative as the nitrene precursor. Cytochrome P450 variant PA-G8 catalyzing this transformation was identified after eight rounds of directed evolution. A variety of 1-aryl-2-alkyl alkynes are accepted by PA G8, including those bearing heteroaromatic rings. This biocatalytic process is efficient and selective (up to 2610 total turnover number (TTN) and 96% ee) and can be performed on preparative scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The origin and formation of oxygen inclusions in austenitic stainless steels manufactured by laser powder bed fusion

The origins of nano-scale oxide inclusions in 316L austenitic stainless steel (SS) manufactured by laser powder bed fusion (L-PBF) was investigated by quantifying the possible intrusion pathways of oxygen contained in the precursor powder, extraneous oxygen from the process environment during laser processing, and moisture contamination during powder handling and storage. When processing the fresh, as-received powder in a wellcontrolled environment, the oxide inclusions contained in the precursor powder were the primary contributors to the formation of nano-scale oxides in the final additive manufactured (AM) product. These oxide inclusions were found to be enriched with oxygen getter elements like Si and Mn. By controlling the extraneous oxygen level in the process environment, the oxygen level in AM produced parts was found to increase with the extraneous oxygen level. The intrusion pathway of this extra oxygen was found to be dominated by the incorporation of spatter particles into the build during processing. Moisture induced oxidation during powder storage was also found to result in a higher oxide density in the AM produced parts. SS 316L powder free of Si and Mn oxygen getters was processed in a well-controlled environment and resulted in a similar level of oxygen intrusion. Finally, microhardness testing indicated that the oxide volume fraction increase from extraneous oxygen did not influence hardness values. However, a marked decrease in hardness was found for the humidified and Si-Mn free AM processed parts.

36 MATERIALS SCIENCE↗

A one-pot synthesis of high-density biofuels through bifunctional mesoporous zeolite-encapsulated Pd catalysts

Developing a powerful bifunctional catalyst for tandem reactions is essential to the future carbon neutrality by reducing the energy consumption in chemical industries. Herein, mesoporous zeolite-encapsulated palladium (Pd) nanoparticles (Pd@meso-ZSM-5) synthesized via emulsification-demulsification followed by a dry-gel transformation method were demonstrated to have a remarkable catalytic performance for a one-pot multiple tandem reaction of cyclic ketones (cyclopentanone, cyclohexanone) to bicyclic alkanes (bicyclopentane, bicyclohexane). Compared with supported catalysts (Pd/meso-ZSM-5) and microporous zeolite-encapsulated catalysts (Pd@ZSM-5) with a primary product of monocyclic alkane (cyclopentane, cyclohexane), Pd@meso-ZSM-5 shows much higher catalytic efficiency for the bicyclic alkanes synthesis, which was previously unattainable in the conventional two-step synthesis route. Controlled experiments and detailed characterizations show that mesoporosity provides sufficient space for the generation and diffusion of large molecular intermediates, and the intimate acid-Pd interface promotes the conversion of intermediates. As a result, this work proposes a design strategy for a mesoporous zeolite-encapsulated metal catalyst, which efficiently provides cooperative acid-hydrogenation catalysis.

09 BIOMASS FUELS↗

Characterization of front contact degradation in monocrystalline and multicrystalline silicon photovoltaic modules following damp heat exposure

Reliability and durability tests play a key role in the photovoltaic (PV) industry by minimizing potential failure risks for both existing and new cell and module technologies. In this work, a detailed study of contact degradation in monocrystalline and multicrystalline PV modules is performed. The modules are subjected to a sequence of damp heat (DH) exposures followed by electrical characterization after each step. Electroluminescence (EL) imaging shows different darkening patterns for monocrystalline modules compared to multicrystalline modules; the former shows darkening near the busbars and the latter shows it across virtually the entire cell surface. The primary loss mechanism is confirmed to be resistive after comparing the current-voltage (I–V) characteristics at each DH exposure step. Representative samples have been cored out from both the degraded modules and controls for materials characterization to gain further insights into the degradation mechanism. Top-down and cross-sectional scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and top-down high-resolution X-ray photoelectron spectroscopy (XPS) analysis performed on the cored samples confirm the degradation is due to metallization corrosion. Our study suggests that the difference in the darkening pattern can most likely be attributed to the different silver paste composition used for contacting each cell technology, particularly the composition of the glass frit.

36 MATERIALS SCIENCE↗

Dynamic substrate reactions during room temperature heavy ion irradiation of CoCrCuFeNi high entropy alloy thin films

Abstract High entropy alloys (HEAs) are promising materials for various applications including nuclear reactor environments. Thus, understanding their behavior under irradiation and exposure to different environments is important. Here, two sets of near-equiatomic CoCrCuFeNi thin films grown on either SiO 2 /Si or Si substrates were irradiated at room temperature with 11.5 MeV Au ions, providing similar behavior to exposure to inert versus corrosion environments. The film grown on SiO 2 had relatively minimal change up to peak damage levels above 500 dpa, while the film grown on Si began intermixing at the substrate–film interface at peak doses of 0.1 dpa before transforming into a multi-silicide film at higher doses, all at room temperature with minimal thermal diffusion. The primary mechanism is radiation-enhanced diffusion via the inverse Kirkendall and solute drag effects. The results highlight how composition and environmental exposure affect the stability of HEAs under radiation and give insights into controlling these behaviors.

36 MATERIALS SCIENCE↗

Electrical Systems of Pumped Storage Hydropower Plants: Electrical Generation, Machines, Power Electronics, and Power Systems

Adjustable-speed (AS) pumped storage hydropower (PSH) technology has the potential to become a large, consistent contributor to grid stability enabling higher penetrations of wind and solar energy on the future U.S. power system. AS-PSH has high-value characteristics, such as fast response to provide ancillary services to the grid, because it is a power converter interface with the grid (like battery storage), but at the same time it has the energy content large enough to supply both short-term (seconds-to-minutes) and long-term (minutes-to-hours) of energy needs, like more conventional power plants. However, designs must be optimized to lower the capital expenditure (CapEx) and to provide a high-quality grid interface capability (e.g. power quality, ancillary service provider, fault-tolerant or fault ride-through capability), which is a primary factor in the acceptance of AS-PSH into a utility’s generation mix. This CapEx will be greatly affected by the cost savings associated with the civil structure, turbine design, power electronics, control systems, or unique generator designs. A holistic design must be considered to get a full picture of the benefits of the technology proposed. The AS-PSH can be controlled to reduce the impact of transient disturbance on a power system and at the same time can be controlled to minimized subsequent component fatigue and potential oscillation modes within the plant, with the overall impact in reducing the operational expenditures (OpEx).Generating clean power to meet standards such as Institute of Electrical and Electronics Engineers (IEEE) 519 and International Electrotechnical Commission (IEC) 1000-3-2 will be a continuing challenge. For many technology developers, however, improved AS-PSH technologies will become a key component of generator-storage systems of the future given the prospects of increased performance and decreasing costs, and the ever-increasing penetration of renewables (e.g wind power and solar power).

13 HYDRO ENERGY↗

Nanosecond Repetitively Pulsed (NRP) Plasmas: Relationship Between Induced Flow and Plasma Characteristics at Atmospheric Pressure (Final Technical Report)

The local flow fields induced by plasma discharges at atmospheric pressure can play a critical role in aerodynamic flow and combustion control and have significant implications for plasma-based technologies in medicine and environmental engineering. However, the coupling between the plasma characteristics, the geometry and the induced flow field is not well understood. The primary goal of this work is to determine the relationship between the plasma characteristics and the induced flow field for nanosecond pulsed discharges at atmospheric pressure. A comprehensive experimental investigation of plasmas produced by nanosecond high-voltage pulses in a pin-to-pin electrode configuration was conducted, employing several measurement techniques including microwave and laser Rayleigh scattering, optical emission spectroscopy, and high-speed imaging. The flow field induced by the nanosecond plasma was measured and characterized using measurements of the velocity (particle image velocimetry) and density (background oriented schlieren) with unprecedented spatiotemporal resolution. The experimental measurements were complemented by development of a one-dimensional model of the plasma discharge and a high-fidelity computational fluid dynamics (CFD) simulation of the subsequent plasma-induced flow field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

3013 Baseline Inner Container Report: Description, Imaging, and Analysis

This report presents consolidated findings from three microscopy studies of baseline Bagless Transfer Containers (BTCs), which are the inner containers used in DOE Standard 3013-compliant plutonium storage packages. The studies were conducted by Los Alamos National Laboratory (LANL), Savannah River National Laboratory (SRNL), and DNV, a subcontractor specializing in corrosion science. The baseline BTCs examined had not been exposed to corrosive environments, serving as control samples for comparison with destructively examined (DE) containers. Additionally, the Background section provides an overview of the BTC design, including manufacturing methods, material properties, and container configurations that may influence corrosion behavior. The primary objective of the LANL and SRNL studies was to establish reference characteristics of BTCs to distinguish manufacturing artifacts from corrosion-induced features observed in DE containers. Both laboratories used advanced microscopy techniques, including Wide Area Microscopy (WAMS), Laser Confocal Microscopy (LCM), Scanning Electron Microscopy (SEM), and Focused Ion Beam (FIB), to reveal that most surface anomalies were shallow and attributable to flow-forming processes, not corrosion. Subsurface impurities, identified as non-metallic inclusions, were also observed. DNV’s investigation focused on characterizing the mechanical and chemical properties of the BTC material to support crack growth modeling. Their findings indicate higher hardness and strength but reduced ductility—consistent with flow-formed 304L stainless steel and a higher-than-expected martensite content, in contrast to manufacturer claims. Ongoing and future studies, including Electron Backscatter Diffraction (EBSD), aim to further understand the microstructural factors influencing crack initiation and propagation. The combined studies provide a crucial baseline for distinguishing corrosion effects in DE containers, contributing to the safe and reliable long-term storage of plutonium-bearing materials.

36 MATERIALS SCIENCE↗

Hafnium Absorber Latching Mechanism Redesign

The poster entails the known problems and updated design solutions for the hafnium absorber latching mechanism. The hafnium absorber latching mechanism is a part of the safety rod system located within ATR's core. The latching mechanism's primary function was to attach hafnium absorbers to the safety rod drive system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Radiosensitizing the Vasculature of Primary Brainstem Gliomas Fails to Improve Tumor Response to Radiation Therapy

Diffuse intrinsic pontine gliomas (DIPGs) arise in the pons and are the leading cause of death from brain tumors in children. DIPGs are routinely treated with radiation therapy, which temporarily improves neurological symptoms but generally fails to achieve local control. Because numerous clinical trials have not improved survival from DIPG over standard radiation therapy alone, there is a pressing need to evaluate new therapeutic strategies for this devastating disease. Vascular damage caused by radiation therapy can increase the permeability of tumor blood vessels and promote tumor cell death.

62 RADIOLOGY AND NUCLEAR MEDICINE↗