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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

ELSI: A unified software interface for Kohn–Sham electronic structure solvers

Solving the electronic structure from a generalized or standard eigenproblem is often the bottleneck in large scale calculations based on Kohn-Sham density-functional theory. This problem must be addressed by essentially all current electronic structure codes, based on similar matrix expressions, and by high-performance computation. We here present a unified software interface, ELSI, to access different strategies that address the Kohn-Sham eigenvalue problem. Currently supported algorithms include the dense generalized eigensolver library ELPA, the orbital minimization method implemented in libOMM, and the pole expansion and selected inversion (PEXSI) approach with lower computational complexity for semilocal density functionals. The ELSI interface aims to simplify the implementation and optimal use of the different strategies, by offering (a) a unified software framework designed for the electronic structure solvers in Kohn-Sham density-functional theory; (b) reasonable default parameters for a chosen solver; (c) automatic conversion between input and internal working matrix formats, and in the future (d) recommendation of the optimal solver depending on the specific problem. As a result, comparative benchmarks are shown for system sizes up to 11,520 atoms (172,800 basis functions) on distributed memory supercomputing architectures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

BEAM COLLIMATION IN THE PIP-II LINAC TO BOOSTER TRANSFER LINE

The new PIP-II superconducting linac will deliver a 2 mA average H⁻ beam to the existing Booster synchrotron. The injected beam is accumulated by charge exchange over approximately 300 turns; phase space painting is used to mitigate space charge effects. To limit the power load on the internal waste beam absorber from the transverse tails of the H⁻ distribution missing the foil, the beam will be collimated in both planes in the linac to Booster transfer line using compact collimators of a novel design. Both the number of parasitic hits and the fraction of the beam missing the foil are sensitive functions of the H⁻ beam centroid position with respect to the edge of the foil. The positioning of the collimation is constrained by the availability of suitable space in the transfer line lattice, by specifics of the collimator design, by the phase space orientation at the collimator, and by the betatron phase advance to the foil needed to achieve proper orientation of the spatial distribution at the injection point. In this contribution, we describe the procedure by which collimator positions were optimized. We then discuss the expected performance of the overall system.

Johnson, David E.↗
DOE OSTI2018

Aerial Assessment of Liquid in Clouds at Oliktok (Final Campaign Report)

Aerial Assessment of Liquid in Clouds at Oliktok (AALCO) Intensive Operation Period (IOP) began in October, 2016 and ended in October, 2017 at the ARM Mobile Facility-3 (AMF-3) at Oliktok Point, Alaska. The operations tested super-cooled liquid water sensors (SLWCs), leaf-wetness sensors, radiosondes, and a distributed temperature sensor (DTS) on tethered balloon system (TBS) platforms throughout the period. An auto-reeler system, a helikite, and a aerostat were tested. When conditions were optimal, the aerostat was preferred to the helikite and the auto-reeler. It was found the SLWCs had better transmission and sensitivity to relay information about the near-surface cloudy boundary layer than the leaf-wetness sensors. The DTS was also found to give useful information about the atmospheric column and deployment is condition-dependent. Results from the SLWCs and DTS are being compared with high resolution Large Eddy Simulations (LES) in the System for Atmospheric Modeling (SAM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Aerial Assessment of Liquid in Clouds at Oliktok Field Campaign Report

The Aerial Assessment of Liquid in Clouds at Oliktok (AALCO) Intensive Operation Period (IOP) began in October 2016 and ended in October 2017 at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) third Mobile Facility (AMF3) at Oliktok Point, Alaska (https://www.arm.gov/research/campaigns/amf2016aalco). The operations tested super-cooled liquid water sensors (SLWCs), leaf-wetness sensors, radiosondes, and a distributed temperature sensor (DTS) on tethered balloon system (TBS) platforms throughout the period. An auto-reeler system, a helikite, and an aerostat were tested. When conditions were optimal, the aerostat was preferred to the helikite and the auto-reeler. It was found that the SLWCs had better transmission and sensitivity to relay information about the near-surface cloudy boundary layer than the leaf-wetness sensors. The DTS was also found to give useful information about the atmospheric column and deployment is condition-dependent. Results from the SLWCs and DTS are being compared with high-resolution large-eddy simulations (LES) in the System for Atmospheric Modeling (SAM) (Khairoutdinov and Randall, 2003).

North Slope of Alaska, Oliktok Point, aerosols, Ar↗
DOE OSTI2017

Optimal Coordinated EV Charging with Reactive Power Support in Constrained Distribution Grids

Electric vehicle (EV) charging/discharging can take place in any P-Q quadrants, which means EVs could support reactive power to the grid while charging the battery. In controlled charging schemes, distribution system operator (DSO) coordinates with the charging of EV fleets to ensure grid’s operating constraints are not violated. In fact, this refers to DSO setting upper bounds on power limits for EV charging. In this work, we demonstrate that if EVs inject reactive power into the grid while charging, DSO could issue higher upper bounds on the active power limits for the EVs for the same set of grid constraints. We demonstrate the concept in an 33-node test feeder with 1,500 EVs. Case studies show that in constrained distribution grids in coordinated charging, average costs of EV charging could be reduced if the charging takes place in the fourth P-Q quadrant compared to charging with unity power factor.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Mitigating Phase Unbalance for Distribution Systems with High Penetrations of Solar PV (Final Technical Report)

Distribution system operators have traditionally limited unbalance among phases by maintaining similar loadings on each phase. High penetrations of distributed solar PV continually change the net loading on each phase, resulting in time-varying phase unbalances that can damage three-phase devices such as three-phase motors, violate grid codes, and increase technical losses. This project has developed several control strategies for the reactive power outputs of solar PV inverters in order to mitigate power quality issues related to phase unbalance. These control strategies include a decentralized approach that is solely based on local measurements, distributed and grouped approaches that consider subsets of loads and PV generators, and a centralized approach that leverages measurements from a variety of locations in order to compute optimal reactive power setpoints for each inverter. Variants of the controllers handle challenges relevant to practical implementations, including noisy measurements, delayed communications, and reactive power limits. Moreover, the project developed theory that provides convergence guarantees for systems with multiple interacting controllers as well as “balanceability” certificates that ensure satisfaction of phase unbalance requirements with variable loading. The controllers were integrated with NRECA’s Open Modeling Framework (omf.coop) and evaluated using actual distribution system models obtained from several NRECA member utilities. Application of the controllers results in significant improvements to phase unbalance in these test cases with decreases from base case levels of over 3% to under 0.5%, which is within the 2% IEC phase unbalance standard.

14 SOLAR ENERGY↗
DOE OSTI2022

Numerical study of advanced solar receiver tubes based on a coupled thermo-mechanical analysis for concentrated solar power tower plant

The search for more sustainable energy to match the growing energy demand begins with finding more dispatchable resources such as solar energy. As one of the promising solar technologies, concentrated solar power (CSP) has a full capacity to store thermal energy for extended operation. Nevertheless, some key components in CSP systems usually face extreme environment, such as uneven solar flux, cyclic thermal expansion, structural degradation on the solar absorber tubes in a Concentrated Solar Power Tower (CSPT) Plant. In this study, we applied Multiphysics simulation to explore the benefits of introducing optimized fins for heat transfer enhancement and uniform temperature distribution, the goal is to improve the thermal efficiency of such advanced solar absorber tubes. The results of this study can supply design guidance for the manufacturing process of absorber tubes, and eventually can benefit the solar energy community for the next generation of molten salt based CSP system.

14 SOLAR ENERGY↗
DOE OSTI2018

Robust state estimation of feeding–blending systems in continuous pharmaceutical manufacturing

State estimation is a fundamental part of monitoring, control, and real-time optimization in continuous pharmaceutical manufacturing. For nonlinear dynamic systems with hard constraints, moving horizon estimation (MHE) can estimate the current state by solving a well-defined optimization problem where process complexities are explicitly considered as constraints. Traditional MHE techniques assume random measurement noise governed by some normal distributions. However, state estimates can be unreliable if noise is not normally distributed or measurements are contaminated with gross or systematic errors. In this paper, to improve the accuracy and robustness of state estimation, we incorporate robust estimators within the standard MHE skeleton, leading to an extended MHE framework. The proposed MHE approach is implemented on two pharmaceutical continuous feeding–blending system (FBS) configurations which include loss-in-weight (LIW) feeders and continuous blenders. Numerical results show that our MHE approach is robust to gross errors and can provide reliable state estimates when measurements are contaminated with outliers and drifts. Finally and moreover, the efficient solution of the MHE realized in this work, suggests feasible application of on-line state estimation on more complex continuous pharmaceutical processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Volume of interest CBCT and tube current modulation for image guidance using dynamic kV collimation

Purpose: The focus of this work is the development of a novel blade collimation system enabling volume of interest (VOI) CBCT with tube current modulation using the kV image guidance source on a linear accelerator. Advantages of the system are assessed, particularly with regard to reduction and localization of dose and improvement of image quality. Methods: A four blade dynamic kV collimator was developed to track a VOI during a CBCT acquisition. The current prototype is capable of tracking an arbitrary volume defined by the treatment planner for subsequent CBCT guidance. During gantry rotation, the collimator tracks the VOI with adjustment of position and dimension. CBCT image quality was investigated as a function of collimator dimension, while maintaining the same dose to the VOI, for a 22.2 cm diameter cylindrical water phantom with a 9 mm diameter bone insert centered on isocenter. Dose distributions were modeled using a dynamic BEAMnrc library and DOSXYZnrc. The resulting VOI dose distributions were compared to full-field CBCT distributions to quantify dose reduction and localization to the target volume. A novel method of optimizing x-ray tube current during CBCT acquisition was developed and assessed with regard to contrast-to-noise ratio (CNR) and imaging dose. Results: Measurements show that the VOI CBCT method using the dynamic blade system yields an increase in contrast-to-noise ratio by a factor of approximately 2.2. Depending upon the anatomical site, dose was reduced to 15%–80% of the full-field CBCT value along the central axis plane and down to less than 1% out of plane. The use of tube current modulation allowed for specification of a desired SNR within projection data. For approximately the same dose to the VOI, CNR was further increased by a factor of 1.2 for modulated VOI CBCT, giving a combined improvement of 2.6 compared to full-field CBCT. Conclusions: The present dynamic blade system provides significant improvements in CNR for the same imaging dose and localization of imaging dose to a predefined volume of interest. The approach is compatible with tube current modulation, allowing optimization of the imaging protocol.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Distribution System State Estimation: A Semidefinite Programming Approach

Distribution system state estimation (DSSE) is one of the vital components in the next-generation distribution management system which allows operators to monitor the entire system's operating conditions. Due to the lack of real-time measurements, DSSE has to process measurements whose quality varies significantly across different sources, which causes a convergence issue to the Gauss-Newton solver. In this paper, a semidefinite programming (SDP) framework is proposed to reformulate the DSSE problem into a rank- constrained SDP problem. One challenge of this technique is the nonconvex rank-one constraint, which is generally relaxed. However, the relaxed SDP-DSSE problem cannot guarantee a rank-one solution and hence loses optimality. Therefore, we propose two solution approaches to obtain rank-one solutions for the SDPDSSE problem: the rank reduction approach and the convex iteration approach. The model and the effectiveness of the proposed solution approaches are numerically demonstrated on the IEEE 13-bus, 34-bus, and 123-bus distribution systems.

convex iteration↗
DOE OSTI2020

Identification of Worst Impact Zones for Power Grids During Extreme Weather Events Using Q-learning

Both the frequency and intensity of extreme weather events have been trending higher in recent years, leading to significant infrastructure damage in the electric grid. The impact of these extreme weather events is desired to be analyzed and quantified to help transmission and distribution system operators prepare for and prevent significant damage and subsequent loss of power. In this paper, we develop an approach that models the impact of extreme weather on the grid and identifies the worst impact zone using Q-learning (a reinforcement learning approach). The identification results reveal grid vulnerability to weather events and provide insights for system operators to help achieve optimal resource allocation and crew dispatch to minimize the adverse impacts of extreme weather. Simulation studies are conducted on the IEEE 123-node system to demonstrate the performance of the proposed approach.

distribution system↗
DOE OSTI2026

iDDS: intelligent distributed dispatch and scheduling for workflow orchestration

The intelligent distributed dispatch and scheduling (iDDS) service is a versatile workflow orchestration system designed for large-scale, distributed scientific computing. iDDS extends traditional workload and data management by integrating data-aware execution, conditional logic, and programmable workflows, enabling automation of complex and dynamic processing pipelines. Originally developed for the ATLAS experiment at the large hadron collider, iDDS has evolved into an experiment-agnostic platform that supports both template-driven workflows and a Function-as-a-Task model for Python-based orchestration. This paper presents the architecture and core components of iDDS, highlighting its scalability, modular message-driven design, and integration with systems such as PanDA and Rucio. We demonstrate its versatility through real-world use cases: fine-grained tape resource optimization for ATLAS, orchestration of large Directed Acyclic Graph (DAG) workflows for the Rubin Observatory, distributed hyperparameter optimization for machine learning applications, active learning for physics analyses, and AI-assisted detector design at the electron–ion collider. By unifying workload scheduling, data movement, and adaptive decision-making, iDDS reduces operational overhead and enables reproducible, high-throughput workflows across heterogeneous infrastructures. We conclude with current challenges and future directions, including interactive, cloud-native, and serverless workflow support.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

An 80-W 94.6%-Efficient Multi-Phase Multi-Inductor Hybrid Converter

This paper presents a new Multi-Phase Multi-Inductor Hybrid (MP-MIH) converter that features high efficiency at large conversion ratios, while operating the switches with duty cycles larger than state-of-the-art hybrid topologies. In this converter, the capacitors are soft-charged and soft-discharged through three inductors operated in three interleaving phases. An experimental six-level three-phase converter prototype achieves 94.6% peak efficiency and 425 W/in 3 power density for conversions from 48V to 1V-2V at loads of up to 40A. This multi-phase multi-inductor hybrid converter architecture can be extended to any number of switched-capacitor network levels to support wide range of input and output voltages and load currents in data centers, telecommunication and other high-performance digital systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

On the Feasibility of Market Manipulation and Energy Storage Arbitrage via Load-Altering Attacks

Around the globe, electric power networks are transforming into complex cyber–physical energy systems (CPES) due to the accelerating integration of both information and communication technologies (ICT) and distributed energy resources. While this integration improves power grid operations, the growing number of Internet-of-Things (IoT) controllers and high-wattage appliances being connected to the electric grid is creating new attack vectors, largely inherited from the IoT ecosystem, that could lead to disruptions and potentially energy market manipulation via coordinated load-altering attacks (LAAs). In this article, we explore the feasibility and effects of a realistic LAA targeted at IoT high-wattage loads connected at the distribution system level, designed to manipulate local energy markets and perform energy storage (ES) arbitrage. Realistic integrated transmission and distribution (T&D) systems are used to demonstrate the effects that LAAs have on locational marginal prices at the transmission level and in distribution systems adjacent to the targeted network.

25 ENERGY STORAGE↗
DOE OSTI2024

Time Dilated Bundt Cake Analysis of PV Output [Poster]

We present a novel method for modeling time-dependent statistics in the power signal generated by a photovoltaic (PV) system. Our white-box machine learning method is interpretable and auditable, based on principles of multiperiodic basis functions and convex optimization. Our proposed method of time dilating the daily signal to remove night time values results in a novel representation of PV power signals, evocative of a ‘Bundt cake’. The proposed model describes the marginal distribution of power output as a function of date and time. The resulting probabilistic model of a PV system can be used to perform a variety of tasks, and here, we demonstrate the application of clear sky detection.

14 SOLAR ENERGY↗
DOE OSTI2020

The Future of Renewable Energy Transmission: An Autonomous Energy Grid

The drastic price reduction in variable renewable energy, such as wind and solar, coupled with the ease of use of smart technologies at the consumer level, is driving dramatic changes to the power system that will significantly transform how power is made, delivered, and used. Distributed energy resources (DERs)—which can include solar photovoltaic (PV), fuel cells, microturbines, gensets, distributed energy storage (e.g., batteries, ice storage), and new loads (e.g., electric vehicles (EVs), light-emitting diode (LED) lighting, smart appliances, and electric heat pumps)—are being added to electric grids and causing bidirectional power flows and voltage fluctuations that can impact optimal control and system operation. Residential solar installations, customer battery systems, and EVs are all seeing rapid increases in deployments. With DER seeing such increased use, it is not unreasonable to imagine a residential electricity customer having at least five controllable DERs. In future electric grids, as more DERs are integrated, the number of active control points will be too much for current control approaches to effectively manage.

30 DIRECT ENERGY CONVERSION↗