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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Designing an Intrusion Detection for an Adjustable Speed Drive System Controlling a Critical Process

In this article, we address the cyber-security problem of industrial control systems (ICSs) when their sensor measurements may be compromised due to an attacker who has intercepted those measurements via a network. We introduce a general-purpose method “Dynamic Watermarking (DW)” to detect potential cyber-intrusions on speed sensor measurements within industrial control systems, which deploy an adjustable speed drive (ASD) to control a critical process. The DW method is injecting a random private low-amplitude signal with a zero mean Gaussian distribution, “watermark”, into one of the input phase voltages powering the ASD system. The watermark signal propagates through the system including pulse width modulation (PWM) power conversion stage and motor, then ultimately appears in the speed sensor measurements. By deploying two statistical DW tests with two proper thresholds, the system can detect potential cyber-intrusions or unobservable cyber-attacks such as replay attacks and false data injection attacks (FDIA). The DW method tested on a laboratory-scale ASD system experimentally to protect the system against cyber-intrusions. This system, powered by a commercial PWM drive operating at 208 V, 3-phase, and 3.7 kW, served as our experimental platform.

42 ENGINEERING↗
DOE OSTI2023

Human Factors for Advanced Reactors

Existing light water reactors in the U.S. are primarily large baseload electricity generating facilities. The concept of operations for these plants remains largely unchanged since the advent of commercial nuclear power—the main control room serves as the hub of plant activities and is staffed with multiple licensed operators who work in tandem under the shift supervisor, and staff such as field workers support the control room remotely. While newer plants have brought the advent of digital human-machine interfaces to replace earlier analog and mechanical instrumentation and controls, much of the control process remains unchanged and manual. It is simply a newer version of legacy concepts. Advanced reactors potentially bring considerable changes to the size, fuel type, automation, and staffing of nuclear power plants, necessitating a fundamental shift not just from analog to digital, but further from human to automation, from onsite to remote, from control to monitoring, and from many to few operators. Despite this multitude of parallel evolutions in reactor designs, many of the vendors developing the next generation of reactors represent smaller research and development enterprises. It is therefore not feasible to address all aspects of plant design at the same time. In particular, the competing design aspects of new reactors present a significant challenge to the development of robust and human factored systems at the plant. As vendors develop new reactor designs, much of the early focus is naturally on the fuel and reactor system technology. Looming behind these early advances is the daunting prospect of first-of-a-kind control concepts that have not yet been developed or validated. A failure to address the human element of reactor design early will lead to missed opportunities. The quickest development process is the replication of existing concepts of operations at legacy plants, even when such systems were long ago surpassed by better human-machine technologies outside the nuclear industry. Conversely, attempting to undertake novel concepts of operations late in the design life cycle of a plant could result in protracted development efforts and delays in licensing and deployment. This does not have to happen, and it is imperative that human factors be considered now, early in the design of new reactors.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Data-driven modeling of power generation for a coal power plant under cycling

Increased penetration of renewables for power generation has negatively impacted the dynamics of conventional fossil fuel-based power plants. The power plants operating on the base load are forced to cycle, to adjust to the fluctuating power demands. This results in an inefficient operation of the coal power plants, which leads up to higher operating losses. To overcome such operational challenge associated with cycling and to develop an optimal process control, this work analyzes a set of models for predicting power generation. Moreover, the power generation is intrinsically affected by the state of the power plant components, and therefore our model development also incorporates additional power plant process variables while forecasting the power generation. We present and compare multiple state-of-the-art forecasting data-driven methods for power generation to determine the most adequate and accurate model. We also develop an interpretable attention-based transformer model to explain the importance of process variables during training and forecasting. The trained deep neural network (DNN) LSTM model has good accuracy in predicting gross power generation under various prediction horizons with/without cycling events and outperforms the other models for long-term forecasting. The DNN memory-based models show significant superiority over other state-of-the-art machine learning models for short, medium and long range predictions. The transformer-based model with attention enhances the selection of historical data for multi-horizon forecasting, and also allows to interpret the significance of internal power plant components on the power generation. This newly gained insights can be used by operation engineers to anticipate and monitor the health of power plant equipment during high cycling periods.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Monitoring Based Commissioning: Step-by-Step Approach to Implementation in Chiller Plants

Chilled water systems consume a significant portion of the energy in manufacturing, and inefficient operation could significantly influence utility bills and the environmental footprint of a facility. One way to ensure long-term energy-efficient plant operation is to ensure that chilled water system equipment, such as chillers, cooling towers, and pumps, are running at their best. Periodic operational assessments help to meet efficiency objectives for cooling plants. However, occasional set point and operational changes resulting from short-term fluctuations cause the plant operation to deviate from optimal. These changes accumulate over time, and operational efficiency deteriorates. Significant energy efficiency improvement potential in chilled water systems can be achieved by operational changes alone. Recent developments in information technology and the industrial internet of things data processing ability have overcome traditional problems and given rise to a new paradigm: monitoring-based commissioning (MBCx). Commissioning platforms and fault detection and diagnostics capabilities have evolved over time and presented more sophisticated abilities to efficiently control process cooling plants. The typical architectures of the MBCx process and a detailed approach to implement the process for chilled water systems are presented. A case study highlighting the energy-and cost-savings potential of MBCx systems is also presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Evaluation of Equiatomic CrMnFeCoNiCu System and Subsequent Derivation of a Non-Equiatomic MnFeCoNiCu Alloy

Investigation into non-equiatomic high-entropy alloys has grown in recent years due to questions about the role of entropy stabilization in forming single-phase solid solutions. Non-equiatomic alloys have been shown to retain the outstanding mechanical properties exhibited by their equiatomic counterparts and even improve electrical, thermal, and magnetic properties, albeit with relaxed composition bounds. However, much remains to understand the processing–structure–property relationships in all classes of so-called high-entropy alloys (HEAs). Here, we are motivated by the natural phenomena of crystal growth and equilibrium conditions to introduce a method of HEA development where controlled processing conditions determine the most probable and stable composition. This is demonstrated by cooling an equiatomic CrMnFeCoNiCu alloy from the melt steadily over 3 days (cooling rate ~4 °C/h). The result is an alloy containing large Cr-rich precipitates and an almost Cr-free matrix exhibiting compositions within the MnFeCoNiCu system (with trace amounts of Cr). From this juncture, it is argued that the most stable composition is within the CrMnFeCoNiCu system rather than the CrMnFeCoNi system. With further optimization and evaluation, a unique non-equiatomic alloy, Mn 17 Fe 21 Co 24 Ni 24 Cu 14 , is derived. The alloy solidifies and recrystallizes into a single-phase face-centered cubic (FCC) polycrystal. In addition to possible applications where Invar is currently utilized, this alloy can be used in fundamental studies that contrast its behavior with its equiatomic counterpart and shed light on the development of HEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Thermodynamic and Kinetic Barriers Limiting Solid-State Reactions Resolved through In Situ Synchrotron Studies of Lithium Halide Salts

Although halide salts such as LiCl and LiBr are routinely used as a source of Li ions during ion exchange reactions, a detailed understanding of the processes controlling the rates of these reactions is presently lacking. Recently, it has been discovered that the rate limiting barriers for ion exchange are commonly associated with these salts rather than the ceramic target of ion exchange, making it important to quantitatively understand of salt processes. Here it is demonstrated that in situ synchrotron studies of ion exchange reactions can be used to precisely quantify the thermodynamic activation energies associated with these solid state reactions in a manner that can be directly compared with predictions from density functional theory (DFT). While the temperature dependence of the LiCl reaction rate is found to be set by a barrier associated with ion hopping, it was discovered that for LiBr it is also affected by the defect formation energy – an energy found to be substantially lower than predicted by DFT. Furthermore, it is shown that when reaction rates for different relative amounts of reactants are varied, it is possible to identify the rate-limiting reagent and to elucidate an overall scaling relationship that controls the concentration-dependence of the reaction rate. Also, it is demonstrated that global fits across doped and undoped salts can be used to probe both intrinsic and extrinsic vacancy concentrations. This improved understanding of ion exchange mechanisms can be used to accelerate ion exchange reaction rates by orders of magnitude. In conclusion, the techniques demonstrated here can be broadly applied to probe the kinetics and thermodynamics of solid state reactions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

SWIFT - Shaped-Waveform Interrogation of Fluids Technique

Researchers at Los Alamos have developed the Shaped-Waveform Interrogation of Fluids Technique (SWIFT), a technology enabling unprecedented process control capability. This technology provides important composition, flow rate, and pipe thickness measurements in real-time, at an extremely low cost and maintenance cycle. By utilizing a specialized shaped-waveform, as well as state-of-the-art signal processing, this information can be gathered without any frequency-domain signal processing, allowing for simplified electronics compared to nearly any other meter on the market. Since this technology is in expensive and non-invasive, with the capability of measuring liquids in both flow pipes and sealed containers, it is perfect for several industrial applications in the oil and gas, beverage, chemical, and pharmaceutical spaces. We are seeking a commercialization partner to license the technology or fund us through a Cooperative Research and Development Agreement (CRADA) to a further develop a usable product for commercial purposes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Planetary Boundary Layer Height (PBLH) over SGP from 1998 to 2023

PBLH is a critical parameter influencing weather phenomena, air quality, and various meteorological processes. However, accurately retrieving PBLH has been a challenging task due to limitations such as coarse temporal resolution and measurement drift in traditional radiosonde observations. To address these limitations, we have devised a lidar-based methodology that capitalizes on a newly developed algorithm for PBLH retrieval. This algorithm demonstrates enhanced capabilities in capturing diurnal fluctuations in PBLH compared to existing lidar-based methods (Su et al. 2020). In addition, we have refined this algorithm specifically for PBLH retrieval under cloudy conditions through a novel scheme (Su et al. 2022). To ensure data reliability, a quality-control process has been implemented to filter out questionable data points. Accompanying the data set is a quality-control flag for ease of reference. It should be noted that we have assimilated all available radiosonde observations to provide a more robust estimate of PBLH, making the data set valuable for a variety of related studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Controlled electrochemical nutrient delivery to enhance marine primary productivity

Oceanic photosynthesis contributes to approximately half of the Earth’s net annual primary productivity. Marine photosynthetic productivity has a high degree of heterogeneity due to spatial and temporal co-limitations of light, temperature, and/or nutrients. Across coastal, near-shore, and open ocean regions, insufficient concentrations of key nutrients (e.g., N, P, Fe) can limit primary productivity. Although studies have shown a significant increase in primary productivity with the addition of low doses of trace nutrients, a sustainable approach to reliably deliver and maintain low doses of nutrients and ensure their bioavailability, remains a challenge. Chemical nutrient addition has relied on the use of chelating agents to ensure nutrient bioavailability, but synthetic chelators are persistent environmental pollutants. In this study, we demonstrate for the first time the use of a controlled electrochemical nutrient delivery (CEND) approach to accelerate the growth of phytoplankton without the need for such chelators. Our study uses commercial stainless-steel electrodes to deliver low concentrations of iron to enhance growth rates in the microalga Picochlorum celeri TG2. To demonstrate the process control offered by the CEND method, we evaluate iron delivery as a function of pulse time, pulse frequency, and rest time between pulses. Our data show that at the same total Fe dose of 163 ppb, electrochemical iron delivery can achieve 9.54 ± 0.58 mg biomass/µg Fe, which is comparable to 9.14 ± 0.17 mg biomass/µg Fe achieved with chemical iron additions that include the synthetic chelating agent ethylenediaminetetraacetic acid (EDTA). Further, when different total iron doses (163 ppb, 325 ppb, and 650 ppb) were delivered over 72 h using CEND, biomass yield per iron dose was higher at lower doses: 9.54 ± 0.58 mg biomass/µg Fe at 163 ppb vs. 4.32 ± 0.32 mg biomass/µg Fe at 650 ppb. This highlights the benefits of CEND in delivering frequent and low doses of nutrients for improved process efficiency. Preliminary assessments show both lower cost and reduced greenhouse gas emissions from electrochemical over chemical iron additions with EDTA. The CEND approach opens new pathways to enhance marine primary productivity, without the unintended environmental impacts of synthetic chelators.

analytical chemistry↗
DOE OSTI2025

Controls Status for Fermilab’s PIP-II Project

Testing of Cryomodule first articles at PIP-II's on-site Cryomodule Test Facility (CMTF), where EPICS based controls are already being used, has been invaluable to the project. In addition to validating hardware and controls components, it has provided opportunities to build buy-in and illicit meaningful feedback early-on. A device naming convention has also been significantly refined with an internal working group and the PIP-II integration team. Compressed air and Process Control Water (PCW) systems have been installed, and operations has been engaged in Phoebus display development in preparation for a transition to operations for these systems by 2026. Cryoplant hardware has been put in place, and collaboration between controls and PIP-IIs cryo group for IOC and display development is well underway for commissioning of cryoplant systems to begin early 2026. The project has also received beneficial occupancy of the High-Bay Building in October 2025, keeping us on schedule for Warm Front End commissioning to begin in 2027.

Crisp, Dan [Fermilab]↗
DOE OSTI2025

Real Time, In-line Monitoring of Hanford Tank Wastes - Year 1 Report

The team comprised of students, postdocs, early, mid and senior career scientists from Los Alamos National Laboratory, Savanah River National Laboratory, Georgia Tech and Florida International University, with the guidance of H2C, is developing a suite of in-line instruments for the Hanford high level waste (HLW) and low active waste (LAW) processes to provide near-real-time analysis of waste form physical properties and composition. The work builds on results from the recent DOE-ORP, EM Technology Development and other projects that demonstrated promise for the use of real-time in-line monitoring (RTIM) to measure chemical compositions of slurries of up to 20 weight % solids. The goal is for this instrument suite is to substantially reduce the need for sampling for process control. Sample waste, exposure associated with sample analysis, and the demand for an external laboratory facility would be greatly reduced. The throughput of waste treatment systems would be improved by elimination of the downtime caused by waiting for sample results. This translates into reduced process storage as process knowledge will be continuously updated in near-real-time. These breakthrough technologies would significantly reduce the life cycle cost and accelerate the schedule for the Hanford tank waste mission.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Revealing the Structural Evolution and Phase Transformation of O3-Type NaNi 1/3 Fe 1/3 Mn 1/3 O 2 Cathode Material on Sintering and Cycling Processes

O-type layered oxide cathode materials can be easily synthesized for a full sodium stoichiometry with high specific capacity, but they all suffer from a capacity fade on cycling. The sintering process control and optimization are critical to ensure a high quality and consistency of the prepared cathode materials with stable structure. Herein, in situ high-energy X-ray diffraction (HEXRD) was first employed to investigate the phase evolution of the oxides during the sintering process of O3-type NaNi 1/3 Fe 1/3 Mn 1/3 O 2 . The in situ HEXRD and both operando Bragg coherent diffraction (BCXD) and coherent multicrystal diffraction (CMCD) were utilized to investigate the phase transformation of the cathode materials during the sodiation/desodiation process. A composite structure comprised of O-type and P-type oxides was formed after the initial electrochemical activation of the cathode material, resulting in good structural and electrochemical stability. This finding implies that strain engineering can be a new design philosophy for the development of next generation high-performance sodium ion cathodes.

25 ENERGY STORAGE↗
DOE OSTI2022

The Impact of Increased Requirements for Verification Measurements of Category III and IV Receipts

As part of the regular nuclear material accounting and control process, sites that have accountable nuclear material regularly perform measurements of the material in their possession. The expectation for the type of measurements and their frequency is set out in Department of Energy (DOE) Order 474.2, and further detailed in each site’s respective material control and accountability (MC&A) plan and associated controlling documents. The measurements of interest in this report are those performed on external (between DOE sites) transfer receipts of Category III or IV accountable materials. In 2020, a revision of DOE Order 474.2 was proposed that would significantly increase the requirement that measurements be performed upon receipt of material, and further, that those measurements be quantitative verification (rather than qualitative confirmatory) measurements. A survey was performed of DOE sites to discuss the impact on their MC&A measurements program if more rigorous verification measurements requirements for Category III and IV receipts were implemented. An assessment of nondestructive assay (NDA) measurement instruments to meet those needs was also performed. Across the board, sites indicated that personnel and budget would cause the largest impact. Sites which are qualified as Category I/II indicated a reduced impact as these sites already have the measurement capabilities and some personnel but would require the acquisition of additional measurement systems. Category III/IV sites indicated a much larger impact as these sites generally have smaller MC&A programs. A few smaller sites stated a measurement program would need to be created to handle the demand. Calorimetry, quantitative gamma spectroscopy and neutron coincidence counting systems were identified as common systems that could meet the verification measurement requirements. The other, and perhaps larger issue is the need for calibration standards for the calorimetry and neutron coincidence counting systems. It is proposed that a comparative study be performed for ISOCS and ISOTOPICS, qualification of a COTS calorimetry system be performed, and development of an AWCC system that uses a neutron generator.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Unsupervised multimodal fusion of in-process sensor data for advanced manufacturing process monitoring

Effective monitoring of manufacturing processes is crucial for maintaining product quality and operational efficiency. Modern manufacturing environments often generate vast amounts of complementary multimodal data, including visual imagery from various perspectives and resolutions, hyperspectral data, and machine health monitoring information such as actuator positions, accelerometer readings, and temperature measurements. However, fusing and interpreting this complex, high-dimensional data presents significant challenges, particularly when labeled datasets are unavailable or impractical to obtain. This paper presents a novel approach to multimodal sensor data fusion in manufacturing processes, inspired by the Contrastive Language-Image Pre-training (CLIP) model. We leverage contrastive learning techniques to correlate different data modalities without the need for labeled data, overcoming limitations of traditional supervised machine learning methods in manufacturing contexts. Our proposed method demonstrates the ability to handle and learn encoders for five distinct modalities: visual imagery, audio signals, laser position (x and y coordinates), and laser power measurements. By compressing these high-dimensional datasets into low-dimensional representational spaces, our approach facilitates downstream tasks such as process control, anomaly detection, and quality assurance. The unsupervised nature of our method makes it broadly applicable across various manufacturing domains, where large volumes of unlabeled sensor data are common. We evaluate the effectiveness of our approach through a series of experiments, demonstrating its potential to enhance process monitoring capabilities in advanced manufacturing systems. This research contributes to the field of smart manufacturing by providing a flexible, scalable framework for multimodal data fusion that can adapt to diverse manufacturing environments and sensor configurations. The proposed method paves the way for more robust, data-driven decision-making in complex manufacturing processes.

Contrastive Learning↗
DOE OSTI2021

Diffusion-to-Imbibition Transition in Water Sorption in Nanoporous Media: Theoretical Studies

The ability to predict multiphase fluid transport in nanoporous rocks such as shales is critical for many geoscience applications, for example unconventional hydrocarbon production, geologic carbon sequestration, and nuclear waste disposal. When the pore sizes approach nanoscales, the impact of the molecular interaction forces between fluids and solids becomes increasingly important. These forces can alter macroscopic fluid phase behavior and control transport. Recent experimental studies have shown that capillary condensation and subsequent imbibition of liquid water can occur in hydrophilic nanoporous media even if the vapor phase is at a critical relative humidity (rhcrit) well below vapor saturation. This study presents a theoretical investigation of the processes controlling adsorption, capillary condensation and imbibition in nanoporous media, using the square-gradient classical density functional theory. The proposed theoretical model explicitly includes the relevant interaction forces among fluids and solids in macroscopic porous media. Application of the model to a relative-humidity-controlled water adsorption experiment is presented to demonstrate the impact of water-pore wall attractive forces on multiphase water behavior in a hydrophilic silicon nanoporous medium. Here, the model represents well the measured time-dependent evolution of the water imbibition front inside the nanoporous medium and also explains the diffusion-like water transport regimes observed at rh < rh crit and the imbibition-like flow regimes observed at rh > rh crit . The study furthermore gives an insight on hysteresis phenomenon in adsorption and desorption isotherms.

58 GEOSCIENCES↗
DOE OSTI2024

Neural lumped parameter differential equations with application in friction-stir processing

Lumped parameter methods aim to simplify the evolution of spatially-extended or continuous physical systems to that of a “lumped” element representative of the physical scales of the modeled system. For systems where the definition of a lumped element or its associated physics may be unknown, modeling tasks may be restricted to full-fidelity physics simulations. Here, in this work, we consider data-driven modeling tasks with limited point-wise measurements of otherwise continuous systems. We build upon the notion of the Universal Differential Equation (UDE) to construct data-driven models for reducing dynamics to that of a lumped parameter and inferring its properties. The flexibility of UDEs allow for composing various known physical priors suitable for application-specific modeling tasks, including lumped parameter methods. The motivating example for this work is the plunge and dwell stages for friction-stir welding; specifically, (i) mapping power input into the tool to a point-measurement of temperature and (ii) using this learned mapping for process control.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Processes contributing to cloud dissipation and formation events on the North Slope of Alaska

Abstract. Clear-sky periods across the high latitudes have profound impacts on the surface energy budget and lower atmospheric stratification; however an understanding of the atmospheric processes leading to low-level cloud dissipation and formation events is limited. A method to identify clear periods at Utqiaġvik (formerly Barrow), Alaska, during a 5-year period (2014–2018) is developed. A suite of remote sensing and in situ measurements from the high-latitude observatory are analyzed; we focus on comparing and contrasting atmospheric properties during low-level (below 2 km) cloud dissipation and formation events to understand the processes controlling clear-sky periods. Vertical profiles of lidar backscatter suggest that aerosol presence across the lower atmosphere is relatively invariant during the periods bookending clear conditions, which suggests that a sparsity of aerosol is not frequently a cause for cloud dissipation on the North Slope of Alaska. Further, meteorological analysis indicates two active processes ongoing that appear to support the formation of low clouds after a clear-sky period: namely, horizontal advection, which was dominant in winter and early spring, and quiescent air mass modification, which was dominant in the summer. During summer, the dominant mode of cloud formation is a low cloud or fog layer developing near the surface. This low cloud formation is driven largely by air mass modification under relatively quiescent synoptic conditions. Near-surface aerosol particles concentrations changed by a factor of 2 around summer formation events. Thermodynamic adjustment and increased aerosol presence under quiescent atmospheric conditions are hypothesized as important mechanisms for fog formation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Forest Canopy Density Effects on Snowpack Across the Climate Gradients of the Western United States Mountain Ranges

Limitations inherent to field studies such as limited spatial and temporal coverage has made it very challenging, if not impossible, to explicitly disentangle the effect of canopy density from climate on snowpack dynamics. Hence, our understanding of how variations in canopy density can affect snow processes under diverse climate conditions has been limited. To address this knowledge gap, this study uses a physics-based modeling approach to represent most key processes that drive snow accumulation and melt in the open and forest with varied forest density, across the climate gradients of the Western U.S. mountain ranges, as represented by 228 Snow Telemetry (SNOTEL) locations. Simulations suggest that, under most winter climate conditions, canopy density exerts a strong influence on under-canopy snowpack dynamics and their controlling processes. Changing canopy density can shift the direction of the modeled differential peak snow accumulation and snow disappearance date (SDD) between the open and forest. For example, while simulated snowpack lasts longer in the open than the high-density forest at most wet/warm and dry/cold locations by up to 55 days, about 90% of all locations show a longer snow duration in the low-density forest by up to 27 days as compared to the open. Interannual variability in climate can also change the magnitude and direction of canopy impact on snow processes. By comparing model simulations to published field observations, and we also identify conditions that require additional field observations to improve process-scale understanding of forest-snow interaction.

54 ENVIRONMENTAL SCIENCES↗