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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Nitrogen and phosphorous acquisition strategies drive coexistence patterns among archaeal lineages in soil

Soil represents the largest reservoir of Archaea on Earth. Present-day archaeal diversity in soils globally is dominated by members of the class Nitrososphaeria. The evolutionary radiation of this class is thought to reflect adaptations to a wide range of temperatures, pH, and other environmental conditions. However, the mechanisms that govern competition and coexistence among Nitrososphaeria lineages in soil remain poorly understood. Here we show that predominant soil Nitrososphaeria lineages compose a patchwork of gene inventory and expression profiles for ammonia, urea, and phosphate utilization. In contrast, carbon fixation, respiration, and ATP synthesis genes are conserved and expressed consistently among predominant phylotypes across 12 major evolutionary lineages commonly found in soil. In situ gene expression profiles closely resemble pure culture reference strains under optimal growth conditions. Together, these results reveal resource-based coexistence patterns among Nitrososphaeria lineages and suggest complementary ecophysiological niches associated with differential nutrient acquisition strategies among globally predominant archaeal lineages in soil.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Light Scattering by a Periodically Corrugated Boundary of a Hyperbolic Medium

The scattering features of radiation incident on a periodically modulated boundary of a hyperbolic medium (HM) are studied numerically. An optimal (in a certain class of functions)—sawtooth—profile shape is found that provides minimum reflection in a wide range of wavelengths. It is shown that, for a certain orientation of the optical axes of the HM, “hot points” appear on the sawtooth boundary, that are responsible for the subwavelength field localization. A generalization is implemented of the numerical method based on the Green’s second identity for the field calculation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

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↗
DOE OSTI2019

Fused Global-Local Economic Model Predictive Control for Real-Time Eco-Optimal Control of a Heavy Duty Truck

This paper introduces a fused global-local economic model predictive control (MPC) with varying time steps for maximizing the fuel economy of a heavy-duty truck, where global MPC is performed over a long horizon using cloud-based dynamic programming (DP), and local MPC is performed on-board the vehicle using sequential quadratic programming (SQP). Because of the computational complexity of DP, an in-depth analysis of how the discretization levels, time constant, and horizon length influence the energy savings and computational complexity of online DP has been performed. The fused optimization technique has been evaluated over different route profiles, accounting for traffic, using a medium-fidelity proprietary Volvo model. Results show 4-7% fuel savings, as compared to a baseline model.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

EFFORT (EFFectiveness Of Rate sTructure for enabling demand response)

This tool helps utilities evaluate potential time of use price-plans and find effective hours for price plan on peak periods and the potential price-elastic demand response. An optimization model can be used to find tiered prices for the time of use tariffs and analyze the impact on load profiles, energy consumption, utility, and customer savings. The tool is equipped with an optimization model to determine the energy consumption of electric appliances that can leverage survey data containing information on the number of appliances owned by customers. Lastly, a statistical model can be used to predict system-level load based on exogenous parameters such as weather, time of day, month, type of day, and year. The tool is scripted in Python and uses the Pyomo python optimization language.

Duwadi, Kapil↗
DOE OSTI2026

A Faster-Than-Real-Time Framework for Reliability-Oriented Simulation of PV Inverters

Physics-of-Failure (PoF) based reliability assessment for photovoltaic (PV) inverters requires long-duration electrical and electrothermal stress histories, yet generating such stress histories with high-fidelity switching models over year long mission profiles is computationally prohibitive. Conventional methods either sacrifice modeling fidelity for speed or require runtimes that are impractical for design iteration and uncertainty studies. To address this bottleneck, this paper presents a High-Performance Computing (HPC) based simulation frame work for faster-than-real-time reliability-oriented simulation. The proposed framework integrates the Average-to-Switching (A2S) method with parallel computing techniques to accelerate switching-level waveform reconstruction. We further introduce optimization strategies, including cluster merging and sensitivity based mission profile screening, to reduce the computational burden. Evaluated using real-world mission profile inputs and a MATLAB/Simulink switching-model reference, the framework reduces the simulation time for a one-year mission from an intractable multi-year duration to approximately 7.3 minutes while maintaining low waveform error. This acceleration provides a practical reliability-oriented simulation engine that can be coupled with component-specific aging models for subsequent PV inverter PoF assessment.

High-performance Computing↗
DOE OSTI2020

Turbulence-parameter estimation for current-energy converters using surrogate model optimization

Surrogate models maximize information utility by building predictive models in place of computational or experimentally expensive model runs. Marine hydrokinetic current energy converters require large-domain simulations to estimate array efficiencies and environmental impacts. Meso-scale models typically represent turbines as actuator discs that act as momentum sinks and sources of turbulence and its dissipation. An OpenFOAM model was developed where actuator disc k-ε turbulence was characterized using an approach developed for flows through vegetative canopies. Turbine-wake data from laboratory flume experiments collected at two influent turbulence intensities were used to calibrate parameters in the turbulence-source terms in the k-ε equations. Additionally, parameter influences on longitudinal wake profiles were estimated using Gaussian process regression with subsequent optimization minimizing the objective function within 3.1% of those obtained using the full model representation, but for 74% of the computational cost (far fewer model runs). This framework facilitates more efficient parameterization of the turbulence-source equations using turbine-wake data.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Development of Control System Functional Capabilities within the IES Plug-and-Play Simulation Environment

The concept of an Integrated Energy System (IES) is meant to combine different energy technologies in synergistic ways to achieve a more secure and economical energy supply. The RAVEN-based HYBRID framework is used to find the optimal installed capacity and the optimal economical dispatch of each component of the IES. A new RAVEN (Risk Analysis Virtual ENvironment) plugin for grid and capacity optimization (HERON) has been developed for optimizing the production variables of the IES given the demand profile. Currently, only the limits that affect the production variables and their corresponding time rates of change are considered (explicit constraints). However, other variables are additionally subject to constraints, but the associated limits are not accounted for (implicit constraints). In particular, for the power dispatch problem, the optimization algorithm takes into account the limits on the electrical power output and the corresponding hourly power variations but does not consider other constraints on process variables whose response effects the service life of the IES. This report describes a scheme that allows accounting for implicit constraints without increasing the size of the optimization problem. The Reference Governor (RG) algorithm is traditionally used for enforcing state and control constraints by modifying the set-point trajectories supplied to the feedback regulators. In our application, the RG is coupled within an iterative loop with the HERON-power dispatcher to generate optimal trajectories that ensure the operational constraints are met. A data-driven procedure to derive a representation of the dynamics of the controlled system was developed. First, the variables that represented the state of the system are selected (PCA-based approach), and then state-space representation matrices are derived from the collected measurements (DMDc algorithm). A preliminary version of the developed workflow based on Linear Time Invariant matrices was assessed by adopting a two-unit test case. More sophisticated versions of this workflow foreseeing the on-line derivation of system matrices will be deployed in FY 2021. Finally, a “plug-and-play” library of controllers and state observers was developed in Dymola. Some aspects of the current configuration of the IES unit components, e.g., the encapsulation of the control schemes into dedicated blocks, are consistent with the “plug-and-play” philosophy. Other features, e.g., the system buses collecting the input and the output variables, are not. For this reason, once listed and described the limits of the current configuration, necessary modifications to the plant model interface are presented. As a test-case, the interfaces of the SES model in the RAVEN-based HYBRID framework were reworked accordingly, and two different control schemes were applied to the same plant model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

AlGaN optimization for photodetectors

AlGaN/GaN-based photodetectors are of great interest for applications involving detection and imaging in the UV–visible wavelength range. In this work we present the results of phototransistors parameters simulation based on Sim Windows for improving efficiency and performance characteristics. We carried the out optimization in active area and an additional doping level profile. The Al mole fraction in the collector and emitter was varied from X = 0.2 to X = 0.3 during simulation. AlGaN-based HPT with an aluminum concentration 28% provides promising performance maximum efficiency with the highest sensitivity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Data-Driven Modeling of High-Resolution Residential Load Profiles Using Low-Resolution Smart Meter Measurements

Accurate and high-resolution residential load profiles are essential for power system modeling, demand response planning, and effective grid operation. As the energy sector moves towards a more actively managed distribution system, the ability to understand residential energy consumption at a minute-by-minute scale becomes increasingly critical. High-resolution load profiles provide key insights into demand patterns and user behavior, enabling grid operators to design more effective energy solutions; however, residential load measurements in the field are typically recorded at low resolutions, such as 15-60 minutes, which makes it hard to study the characteristics of different residential customers. This paper addresses these challenges by introducing a data-driven approach to generate realistic, high-resolution residential load profiles based on lowre-solution measurements and weather information. The proposed method retains the key features of the actual residential load measurements while offering appliance-level energy consumption details for each residential building. The results demonstrate the effectiveness of the proposed load profile generator, proving its capability to support utilities in optimizing residential energy management and ensuring a more reliable and resilient grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

JTAG-based PLC memory acquisition framework for industrial control systems

In industrial control systems (ICS), programmable logic controllers (PLC) are the embedded devices that directly control and monitor critical industrial infrastructure processes such as nuclear plants and power grid stations. Cyberattacks often target PLCs to sabotage a physical process. A memory forensic analysis of a suspect PLC can answer questions about an attack, including compromised firmware and manipulation of PLC control logic code and I/O devices. Given physical access to a PLC, collecting forensic information from the PLC memory at the hardware-level is risky and challenging. It may cause the PLC to crash or hang since PLCs have proprietary, legacy hardware with heterogeneous architecture. This paper addresses this research problem and proposes a novel JTAG (Joint Test Action Group)-based framework, Kyros, for reliable PLC memory acquisition. Kyros systematically creates a JTAG profile of a PLC through hardware assessment, JTAG pins identification, memory map creation, and optimizing acquisition parameters. It also facilitates the community of interest (such as ICS owners, operators, and vendors) to develop the JTAG profiles of PLCs. Further, we present a case study of Kyros implementation over Allen-Bradley 1756-A10/B to help understand the framework's application on a real-world PLC used in industry settings. The sample PLC memory dumps are shared with the research community to facilitate further research.

Rais, Muhammad Haris↗
DOE OSTI2025

The scoping, design, and plasma physics optimization of the Eos neutron source stellarator

On the path to a fusion pilot plant, Thea Energy plans to build Eos, a sub-breakeven, deuterium-deuterium, beam-target fusion, stellarator neutron source facility for producing tritium and other valuable radioisotopes. In this paper, a set of 1D plasma physics models are coupled and used to design the operating point of the facility and predict performance. At this foundational stage of the design, analytic and approximate models are sufficient to capture the leading-order effects, and fast enough to run in the inner loop of an optimizer. Higher-fidelity analyses will follow. Models of 1D profile-dependent neutral beam stopping, ion beam slowing down, beam-target fusion, electron-ion classical heat transfer, energy confinement (ISS04), beam pressure, beam heating of ions and electrons, beam-beam fusion fraction, and neutral beam injection and gyrotron heating electrical efficiencies are included. A numerical optimizer is used to determine the minimum required facility electric power to generate tritium at a given rate. A potentially advantageous regime is described in which modern precisely-quasisymmetric stellarators, new high-temperature superconductors, ITER-derived neutral beam injection, and new high-frequency gyrotrons enable a suitible target plasma with hot electrons, cold ions, peaked density and temperature profiles, and high beam-injected ion density. It appears possible at this time for a facility with a medium-scale and medium-strength stellarator whose required facility electric power is less than 40 MW to produce $2.5\times 10^{17}$ neutrons s -1 for the production of radioisotopes. With the addition of a tritium breeding blanket, such a facility could produce 0.2 grams d -1 or 70 grams yr -1 of tritium.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Fast model-based scenario optimization in NSTX-U enabled by analytic gradient computation

Model-based optimization offers a systematic approach to advanced scenario planning. In this case, the feedforward-control inputs (actuator trajectories) that are needed to attain and sustain a desired scenario are obtained by solving a nonlinear constrained optimization problem. This class of problems generally minimize a cost function that measures the difference between desired and actual plasma states. Several numerical optimization algorithms, such as sequential quadratic programming, require repeated calculation of the cost function gradients with respect to the input trajectories. Calculating these gradients numerically can be computationally intensive, increasing the time needed to solve the feedforward-control optimization problem. Here, this work introduces a method to analytically calculate these cost function gradients from the current profile evolution model. This can significantly reduce the computational time and allow for fast feedforward-control optimization, which would eventually enable optimal scenario planning between discharges. The performance of the feedforward optimizer with analytical gradients is compared to a traditional optimization algorithm based on numerical gradients for different NSTX-U scenarios. The plasma dynamics in the optimization algorithm are simulated using the Control Oriented Transport SIMulator (COTSIM). Results of the work show that analytical gradients consistently reduce the computation time while achieving trajectories that are comparable to those obtained by traditional optimization algorithms based on numerical gradients.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

A Framework for Optimal Placement of Rooftop Photovoltaic: Maximizing Solar Production and Operational Cost Savings in Residential Communities

Optimizing the placement of photovoltaic (PV) panels on residential buildings has the potential to significantly increase energy efficiency benefits to both homeowners and communities. Strategic PV placement can lower electricity costs by reducing the electricity fed from the grid during on-peak hours, while maintaining PV panel efficiency in terms of the amount of solar radiation received. In this article, we present a framework that identifies the ideal location of PV panels on residential rooftops. Our framework combines energy and environmental simulation, parametric modeling, and optimization to inform PV placement as it relates to and affects the entire community (in terms of both energy use and financial cost), as well as individual buildings. Ensuring that our framework accounts for shading from nearby buildings, different utility rate structures, and different buildings’ energy demand profiles means that existing communities and future housing developments can be optimized for energy savings and PV efficiency. The framework comprises two workflows, each contributing to optimal PV placement with a unique target: (a) maximizing PV panel efficiency (i.e., solar generation) and (b) minimizing operational energy cost considering utility rate structures for operational energy. We apply our framework to a residential community in Fort Collins, Colorado, to demonstrate the optimal PV placement, considering the two workflow targets. Here, we present our results and illustrate the effect of PV location and orientation on solar energy production efficiency and operational energy cost.

14 SOLAR ENERGY↗
DOE OSTI2021

Magnetic-Confinement Fusion—Plasma Theory: Tokamak Magnetohydrodynamic Equilibrium and Stability

Magnetohydrodynamics (MHD) provides a useful model to describe the crucial plasma macroscopic equilibrium and stability behaviors in toroidal tokamak devices by considering the plasma as a conducting fluid interacting with a surrounding confining electromagnetic field. MHD is the most basic plasma model, incorporating most large-scale phenomena, including plasma equilibrium and all major instabilities. MHD equations are obtained by taking moments of the Boltzmann equations for different plasma species. They provide a set of comprehensive physics constrains to compute and optimize the equilibrium plasma shape and pressure and current profiles that are critical to its stability and performance. In the ideal case, the equations have special properties that lead to efficient numerical calculation schemes, the most important of which is the ideal MHD energy principle for linear stability against small departures from equilibrium. In a tokamak plasma, equilibrium pressure is mostly destabilizing for MHD modes, whereas equilibrium current is also often a major driving force. Plasma resistivity creates new freedom for a MHD instability to grow, but there are also cases where the plasma resistivity plays a stabilizing role. Equilibrium toroidal flow and/or flow shear can affect MHD instabilities. Principal MHD instabilities include the internal kink mode, sawtooth, fishbone, external kink, resistive wall mode, resistive interchange, tearing and neoclassical tearing modes (NTMs), locked modes, toroidal Alfven eigenmodes (TAEs), and edge localized modes (ELMs). Fast-growing MHD instabilities can lead to an abrupt plasma disruption and termination that can potentially damage the device plasma facing components (PFCs) and in-vessel structures. Furthermore, an important MHD application is to develop robust techniques to mitigate and control MHD instabilities.

Dispersive pellet injection↗
DOE OSTI2023

Utilization of ACE nuclear data file toolkit ACEtk to calculate relative sensitivity coefficients of point-kinetics parameters

Sensitivity and uncertainty methods are quintessential for nuclear criticality safety and experiment design. This type of analysis relies on calculations of sensitivity coefficients; sensitivity coefficients of the effective neutron multiplication factor with respect to some nuclear data are predominantly calculated and used. As a part of the Laboratory Directed Research & Development project EUCLID (Experiments Underpinned by Computational Learning for Improvements in nuclear Data) at Los Alamos National Laboratory, sensitivity coefficients of many radiation detector measurement responses with respect to nuclear data were investigated. Specifically, this paper outlines a method to calculate point-kinetics parameters relative sensitivity coefficients with respect to nuclear data. Point-kinetics parameters such as the prompt neutron decay constant, effective delayed neutron fraction, and neutron generation time are especially important to experimenters and reactor operators designing systems with dynamic neutron populations. This method couples capabilities of the ACE (A Compact ENDF) nuclear data file toolkit, ACEtk, with the ability to load cross sections into the radiation transport code Monte Carlo N-Particle (MCNP). In conclusion, key aspects of optimizing this method for a particular application and sensitivity profiles of the Jezebel criticality experiment are examined and discussed.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Optimizing district energy systems under uncertainty: Insights from a case study from Washington D.C., USA

This study investigates solutions for delivering affordable heating and cooling to a brownfield site, focusing on a case study in Washington, DC. Moving towards more diverse and resilient energy systems, we identify the optimal portfolio for a district energy system with diverse energy sources to meet the area’s energy demands. Our methodological approach integrates two detailed models: one calculating building-level energy demand and the other optimizing district energy technology choices based on their demand profiles, accounting for uncertainties in energy prices, policies, and other parameters. The results provide an economic comparison of district and individual supply options at the building level, emphasizing the flexibility district systems can offer to the electricity sector. District energy systems demonstrate cost-stabilization benefits amidst volatile energy prices and external uncertainties. For heating, district systems yield significant cost savings compared to individual solutions, driven by fuel flexibility and the use of local renewable energy sources. For cooling, district systems also show advantages, though individual systems may remain more cost-effective for smaller buildings. Additionally, district systems exhibit considerable flexibility on the heating side, as evidenced by variations in electricity consumption. We recommend future research to explore the relationship between the economics of district energy systems, particularly at the building level, and their flexibility potential for the electricity sector across diverse geographic contexts to reduce overall grid costs and promote grid reliability. This includes areas with distinct zoning laws, municipal priorities, utility structures, and funding mechanisms, such as the United States, and regions like Europe with pronounced electricity price volatility.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Homo- and hetero-dimeric subunit interactions set affinity and efficacy in metabotropic glutamate receptors

Metabotropic glutamate receptors (mGluRs) are dimeric class C G-protein–coupled receptors that operate in glia and neurons. Glutamate affinity and efficacy vary greatly between the eight mGluRs. The molecular basis of this diversity is not understood. We used single-molecule fluorescence energy transfer to monitor the structural rearrangements of activation in the mGluR ligand binding domain (LBD). In saturating glutamate, group II homodimers fully occupy the activated LBD conformation (full efficacy) but homodimers of group III mGluRs do not. Strikingly, the reduced efficacy of Group III homodimers does not arise from differences in the glutamate binding pocket but, instead, from interactions within the extracellular dimerization interface that impede active state occupancy. By contrast, the functionally boosted mGluR II/III heterodimers lack these interface ‘brakes’ to activation and heterodimer asymmetry in the flexibility of a disulfide loop connecting LBDs greatly favors occupancy of the activated conformation. Our results suggest that dimerization interface interactions generate substantial functional diversity by differentially stabilizing the activated conformation. This diversity may optimize mGluR responsiveness for the distinct spatio-temporal profiles of synaptic versus extrasynaptic glutamate.

59 BASIC BIOLOGICAL SCIENCES↗