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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Scaling Deep Energy Retrofits for Residential Walls - Energy, Cost, and Economic Assessment of Five Wall Systems

Providing strong economic and performance value is a primary challenge of convincing homeowners to implement deep energy retrofits to their wall systems. This study combines energy modeling and technoeconomic assessment of six experimental residential retrofit wall systems to typical existing homes in cold climates to evaluate their energy performance and cost effectiveness. Deep energy retrofits can significantly improve the energy performance of a home’s thermal envelope, help manage indoor environmental pollutants, increase homeowner comfort, increase building value, and register significant energy and cost savings in the process. We are evaluating exterior wall retrofit components and construction practices to measure and recommend steps to improve financial performance for manufacturers, installers and consumers. This study leverages a literature review, inputs from an advisory group made up of thermal enclosure experts, and simulations to identify state-of-the-art technologies for energy efficient wall systems that are suitable for cold and very cold climate zones. This paper will present results from energy modeling of six experimental wall systems compared to one baseline, that inform cost and energy performance of the subject wall systems.

Ganguli, Sumitrra↗
DOE OSTI2025

Laboratory Testing and Performance Characterization of the High Efficiency Dehumidification System (HEDS) Technology

The high efficiency dehumidification system (HEDS) is a unique air handling unit (AHU) design with two water coils. Connected in series, these water coils can sensibly reheat the airstream after it is cooled and dehumidified, thereby mitigating (or sometimes eliminating) the need for conventional sensible reheat with additional energy from hot water, electric resistance or steam coils. Another unique design feature is the size of the HEDS primary cooling coil. While typical AHU cooling coils have a 6-row geometry, the HED's cooling coil has a deeper 10-row geometry enabling discharge air dew point temperatures at or below 55 degrees F despite warmer chilled water supply temperatures approaching (sometimes exceeding) 50 degrees F. The ability to meet acceptable discharge air dew points with warmer chilled water supply temperatures improves both operational efficiency and system resilience against chilled water plant operational or control issues. This report summarizes the 59 steady-state test results that form a comprehensive performance map of the HEDS technology including its reheat capability. The breadth of outdoor air conditions and flow rates over which the HEDS technology was tested and characterized encompasses the unit 1) operating as a dedicated outdoor air system or mixed air system and 2) controlled with constant air volume or variable air volume fan control.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Extreme Weather Events and PV Systems Impact

The impact of extreme weather events on PV performance was studied by comparing the National Oceanic and Atmospheric Administration database on severe weather with the National Renewable Energy Laboratory's (NREL) PV Fleet database on continuous PV performance. We identified 170 systems that were immediately impacted by weather events. These severe weather events lead to a median loss of only 1 % of annual production. However, flooding and high wind events were found to have an extremely long tail extending to 60 % loss, showing that these discrete events can pose a substantial risk to PV systems. Besides the short-term impact of lost production due to outages, we also found a statistically significant increased performance loss rate (PLR) for high wind events above 90 kilometer/hour, by comparing PLR before and after these events. Similarly, hail events caused higher PLR for hail sizes of and above 25 mm indicating that more stringent hail testing for PV modules is required. In addition, very high snow loads may also cause increased PLRs, but more data are required to better quantify the impact. These findings illustrate the substantial risk extreme weather events pose short-and long-term to fielded PV installations.

extreme weather↗
DOE OSTI2025

Thermal and Well Flow Performance of Closed-Loop Geothermal in the Wattenberg Area

Closed-loop geothermal systems provide an alternative to resource-constrained hydrothermal systems and stimulation-intensive enhanced geothermal systems. In this work, we apply the slender-body theory (SBT) model, to simulate the well flow and heat transfer performance of U-loop well designs in the Wattenberg area of the Denver-Julesburg Basin. Three U-loop well patterns are investigated, including a single-, double-, and multi-lateral design. The subsurface within the area of interest is characterized by deep, hot (> 200 degrees C) igneous/metamorphic basement rock underlying multiple sedimentary formations. The lateral section(s) of the U-loop lie(s) within a target depth of 6 km, where temperatures are estimated to approach 300 degrees C. As a base case, conduction-only heat transfer is investigated through simulations with the SBT model within U-loops with open-hole laterals that exchange heat directly with the hot, dry rock using water as a working fluid. The utilization of supercritical CO2 as a heat transfer fluid is also considered. For each scenario, the system performance in terms of annual heat production and temperature profile over a 20-year project lifetime are assessed. Also, the levelized costs of heat and electricity (LCOH and LCOE) are determined using a top-down techno-economic analysis model. The results show that the performance- and cost-optimized U-loop design is one having an injection-production well spacing of 1,000 meters with ten 50-meter-spaced laterals that traverse a subsurface system with a temperature gradient of 60 degrees C/km. By injecting 20 degrees C-water at a rate of 60 kg/s through this loop, an average heat production of 19 MWth (i.e., 2.2 MWe net plant output) can be achieved, resulting in an LCOE and LCOH of $136/MWhe and $1.53/GJ, respectively, over a 20-year project life.

closed-loop geothermal↗
DOE OSTI2021

Modeling the Fundamental Radiation Chemistry of the Organic Diluent, and the Effect of Metal Ion Complexation on the Radiochemical Behavior of Active Compounds

All used nuclear fuel (UNF) reprocessing technologies must operate efficiently in the presence of an intense, multi-component (predominantly alpha, beta, and gamma) radiation field. Consequently, radiation-induced degradation of reprocessing systems is of concern, as it negatively impacts process performance over time due to the destruction of both active compounds (ligands, phase modifiers, holdback agents, etc.) and the formation of degradation products. Reprocessing solvent system radiolysis has been linked to changes in separation efficiency and physical properties of solvent mixtures, solvent-recycle longevity, crud formation, and other unexpected outcomes that impact the efficient recovery of valuable materials (e.g., the actinides) and the volume of hazardous radioactive waste for final disposal, i.e., in a geological repository. Consequently, a fundamental understanding of radiolytic processes and their effects on reprocessing solvent system performance is critical for: (i) the cost-effective development and innovation of separation technologies; (ii) the design and implementation of predictive radiation chemical models for process monitoring and lifetimes; and (iii) potentially the ability to exploit radiolytic phenomenon to our benefit, e.g., strategic radiolysis of active molecules to liberate specific degradation products that aid subsequent process stages. Despite extensive investigation into the radiolytic behavior of active solvent system compounds, little attention has been given to understanding (i) the radiation chemical behavior and modification of the organic diluent and (ii) the effect of metal ion complexation on the radiochemical behavior of active compounds.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

A Year-Round Energy-Efficient Fresh Air Handling System with Two-Stage Heat Pumps and Lake Water Pre-Treatment

Supplying fresh air is important for indoor air quality, but the energy consumption to treat fresh air is significant. The main problems in existing fresh air system include: supplying single-temperature water to treat fresh air and not applying natural energy sufficiently restrict the efficiency improvement of cooling and heat sources; unused air handling devices under most operating conditions throughout the year increase the fan energy consumption. Thus, this study proposes an efficient fresh air system that uses lake water to pre-treat fresh air and two-stage heat pumps for further treatment, and the unused air handling devices in the system are bypassed. A fresh air system in northern China is selected as a case to show the annual energy performance of the proposed system, and a comparative analysis is conducted between the proposed system and a traditional system. The results show that the annual energy-savings of the proposed system compared to the traditional system come from fans, and compressors, which are 56.5%, and 31.1%, respectively, with an entire system energy saving of 32.2%. The proposed system can achieve an annual system coefficient of performance (COP) of 5.5. This study provides potential for further improving the energy efficiency in fresh air treatment.

Liang, Chenjiyu↗
DOE OSTI2024

pnnl/oedisi_dopf

OpenEDI - System Integration (OEDI-SI) - PNNL Distributed Optimal Power Flow (DOPF)

Slay, Tylor↗
DOE OSTI2024

Ginkgo - A math library designed to accelerate Exascale Computing Project science applications

Large-scale simulations require efficient computation across the entire computing hierarchy. A challenge of the Exascale Computing Project (ECP) was to reconcile highly heterogeneous hardware with the myriad of applications that were required to run on these supercomputers. Mathematical software forms the backbone of almost all scientific applications, providing efficient abstractions and operations that are crucial to harness the performance of computing systems. Ginkgo is one such mathematical software library, nurtured by ECP, providing high-performance, user-friendly, and performance portable interfaces for applications in ECP and beyond. In this paper, we elaborate on Ginkgo’s philosophy of high-performance software that is sustainable, reproducible, and easy to use. We showcase the wide feature set of solvers and preconditioners available in Ginkgo and the central concepts involved in their design. We elaborate on four different ECP software integrations: MFEM, PeleLM + SUNDIALS, XGC, and ExaSGD that use Ginkgo to accelerate their science runs. Performance studies of different problems from these applications highlight the effectiveness of Ginkgo and the benefits incurred by these ECP applications.

Cojean, Terry↗
DOE OSTI2021

U.S. Solar Photovoltaic System and Energy Storage Cost Benchmark (Q1 2020)

This report benchmarks U.S. solar photovoltaic (PV) system installed costs as of the first quarter of 2020 (Q1 2020). We use a bottom-up method, accounting for all system and project-development costs incurred during the installation to model the costs for residential (with and without storage), commercial (with and without storage), and utility-scale systems (with and without storage). We also incorporate other system characteristics and performance factors, as well as ongoing costs, to benchmark LCOE for PV-standalone systems, and LCOSS for solar+storage.

14 SOLAR ENERGY↗
DOE OSTI2023

Sensitivity and Importance Measure Analyses for Various Design Architectures for High Safety-Significant Safety-Related Digital Instrumentation and Control Systems of Nuclear Power Plants

A transition from analog instrumentation and control (I&C) technologies to digital I&C technologies is taking place for license renewals of existing nuclear power plants and for operating licenses of new advanced reactors. This transition necessitates research on risk and economic assessments of digital I&C technologies to ensure the long-term safety and reliability of vital systems, reduce uncertainty in licensing costs in addition to timeline, support integration of digital I&C systems in the plant, and find the most efficient technology upgrades. Adding redundancy within systems or components is a common means of improving design safety; however, it can also make designs more prone to common-cause failures (CCFs). Introducing diversity into redundant systems or components is a way to mitigate and possibly eliminate CCFs, but it also increases plant complexity and may be costly. The balance between redundancy and diversity remains a challenge for digital I&C systems. This study performs sensitivity and importance analyses for four design architectures of two digital I&C systems—the reactor-trip system and the engineered safety features actuation system. For each system, two architectures are examined, including a redundant, non-diverse configuration and a redundant, diverse configuration. The sensitivity analysis will provide insights on the impact of introducing diversity to system reliability. The importance results will help identify risk-significant and risk-sensitive components and failure modes, which may be good candidates for future design improvement.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Transactive HVAC Agent - Design and Performance Evaluation

Transactive energy systems are playing an increasingly important role in the efficient and reliable marketbased operation of the power grid. Since a significant portion of the residential building energy consumption is from heating ventilation and air conditioning (HVAC) systems, HVAC is one of the most promising resources to provide load flexibility. However, utilizing HVAC flexibility to provide various grid services while simultaneously maintaining consumer comfort and cost-reductions is challenging. This paper presents a design of a transactive HVAC agent (T-HVAC) to be used as a supervisory control for the HVAC system that can simultaneously ensure comfort and cost-reduction. In particular, the T-HVAC a) estimates HVAC thermal dynamics, b) ensures optimal operations of the HVAC system, and c) participates into markets, and d) implements a market-based control via controlling the thermostat temperature set-point. The T-HVAC performance is demonstrated through multiple scenarios and illustrations.

Demand flexibility, distribution system, HVAC, Tra↗
DOE OSTI2021

Hollow electron lenses for beam collimation at the High-Luminosity Large Hadron Collider (HL-LHC)

Electrons lenses produce a high-intensity electron beam and have a variety of applications to circular hadron accelerators. Electron beams of different transverse cross sections and distributions may be designed, depending on the desired application, and they are produced and steered along the orbit of the hadron beam, overlapping with it for typical distances of a few meters before being deflected away and disposed of. Hollow electron beams find applications to high-intensity beam collimation for machines like the CERN Large Hadron Collider (LHC). Such devices can be integrated in a collimation system to improve the halo-cleaning performance through an active control of the halo dynamics: the annular distribution of the electrons excites resonantly the beam tails surrounding the beam core, while the core itself remains unperturbed, as ideally it only “sees” the field-free “hole” in the electron distribution. Hollow electron lenses are part of the upgrade baseline of the High-Luminosity project of the LHC (HL-LHC) and will be installed in the machine during a long shutdown in 2025–2027 to mitigate effects from beam losses so to improve the collimation system performance. This paper describes the hollow electron lens project within the HL-LHC collimation upgrade.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Experimental Investigation on Heating Performance of a Cold Climate Thermoelectric-Assisted Heat Pump

To accelerate the electrification of air source heat pumps (ASHPs) in cold climates across the United States, various initiatives have been launched to enhance the effectiveness of ASHPs. One avenue of research involves incorporating thermoelectric (TE) technology into vapor compression refrigeration cycles. This study aims to assess the heating performance of a cold climate ASHP by employing TE modules as a liquid line subcooler. The tested system is a nominal 4.5-ton split heat pump utilizing R410A, equipped with a scroll compressor and an accumulator. An electronic expansion valve was employed for both cooling and heating modes. Two configurations of TE sub-coolers, one utilizing 2 TE bundles and the other 4 TE bundles, were integrated into the liquid line of the tested system. The heating performance of these configurations was evaluated. The results revealed that activating the TE subcooler led to a notable increase in total heat capacity, reaching 1318 W at -15.0 °C and 1164 W at -19.0 °C. The corresponding TE coefficients of performance (COPs) were 1.76 and 1.63, respectively. The activation of the TE sub-cooler resulted in a slight reduction in the overall system COP, with a decrease ranging from -2.6% to -4.2% for these two temperatures. The system COPs were measured at 2.10 and 1.86 for -15.0 °C and -19.0 °C, respectively. This prototype demonstrated a significant augmentation in heating capacity with a minimal sacrifice in COP.

Hu, Yifeng↗
DOE OSTI2020

HIDES: Hybrid Intrusion Detector for Energy Systems

The establishment of a resilient electric grid accompanied by a secure communications network is an ongoing battle as advanced persistent threats continue to exploit existing vulnerabilities in legacy supervisory control and data acquisition system (SCADA) infrastructure. Traditional intrusion detection systems (IDSs) lack consistent performance because of the continuously evolving attack surface of SCADA systems. These shortcomings can be overcome by integrating logical system behavior, protocol-specific knowledge, and data-based learning to develop a comprehensive IDS solution. In this paper, we present a Hybrid Intrusion Detector for Energy Systems by integrating a network-based IDS, state-of-the-art machine learning-based IDS, and model-based IDS to detect unknown and stealthy cyberattacks targeting the SCADA networks. The proposed IDS uses synchrophasor measurements and cyber logs to learn patterns of different scenarios based on spatiotemporal behaviors of power systems. As a proof of concept, we implement and validate the proposed IDS by leveraging resources available at the National Renewable Energy Laboratory's Energy Systems Integration Facility test bed. Experimental results show promising performance in detecting cyberattacks while providing realtime visualization of power system measurements and cyber logs.

machine-learning intrusion detection system↗
DOE OSTI2024

Evaluating the potential of disaggregated memory systems for HPC applications

Summary Disaggregated memory is a promising approach that addresses the limitations of traditional memory architectures by enabling memory to be decoupled from compute nodes and shared across a data center. Cloud platforms have deployed such systems to improve overall system memory utilization, but performance can vary across workloads. High‐performance computing (HPC) is crucial in scientific and engineering applications, where HPC machines also face the issue of underutilized memory. As a result, improving system memory utilization while understanding workload performance is essential for HPC operators. Therefore, learning the potential of a disaggregated memory system before deployment is a critical step. This paper proposes a methodology for exploring the design space of a disaggregated memory system. It incorporates key metrics that affect performance on disaggregated memory systems: memory capacity, local and remote memory access ratio, injection bandwidth, and bisection bandwidth, providing an intuitive approach to guide machine configurations based on technology trends and workload characteristics. We apply our methodology to analyze thirteen diverse workloads, including AI training, data analysis, genomics, protein, fusion, atomic nuclei, and traditional HPC bookends. Our methodology demonstrates the ability to comprehend the potential and pitfalls of a disaggregated memory system and provides motivation for machine configurations. Our results show that eleven of our thirteen applications can leverage injection bandwidth disaggregated memory without affecting performance, while one pays a rack bisection bandwidth penalty and two pay the system‐wide bisection bandwidth penalty. In addition, we also show that intra‐rack memory disaggregation would meet the application's memory requirement and provide enough remote memory bandwidth.

Ding, Nan↗
DOE OSTI2020

Towards Interactive, Reproducible Analytics at Scale on HPC Systems

The growth in scientific data volumes has resulted in a need to scale up processing and analysis pipelines using High Performance Computing (HPC) systems. These workflows need interactive, reproducible analytics at scale. The Jupyter platform provides core capabilities for interactivity but was not designed for HPC systems. In this paper, we outline our efforts that bring together core technologies based on the Jupyter Platform to create interactive, reproducible analytics at scale on HPC systems. Our work is grounded in a real world science use case-applying geophysical simulations and inversions for imaging the subsurface. Our core platform addresses three key areas of the scientific analysis workflow-reproducibility, scalability, and interactivity. We describe our implemention of a system, using Binder, Science Capsule, and Dask software. We demonstrate the use of this software to run our use case and interactively visualize real-Time streams of HDF5 data.

containers↗
DOE OSTI2026

Near-Optimal Performance of Stochastic Model Predictive Control

Here, this article presents a regret analysis for stochastic model predictive control (SMPC) in linear systems with quadratic performance index and additive and multiplicative uncertainties. Under a finite support assumption, the problem can be cast as a finite-dimensional quadratic program, but the problem becomes quickly intractable as the problem size grows exponentially in the horizon length. SMPC aims to compute approximate solutions by solving a sequence of problems with truncated prediction horizons and committing the solution in a receding-horizon fashion. Although this approach is widely used in practice, its performance relative to the optimal solution is not well understood. This article reports for the first time a rigorous near-optimal performance guarantee of SMPC: under stabilizability and detectability conditions, the regret of SMPC is exponentially small in the prediction horizon length, allowing SMPC to achieve near-optimal performance at a substantially reduced computational expense.

93E20, 93B45↗
DOE OSTI2023

IEA PVPS Task 13 Techno-Economic Study of Bifacial Photovoltaic Systems on Single Axis Trackers

The International Energy Agency PVPS Task 13 has assembled an international team of photovoltaic (PV) researchers from government labs, academia, and industry to study the specific application of bifacial PV modules deployed on tracking systems. This configuration is of particular interest as it has been identified as the PV system design with the lowest Levelized Cost of Electricity (LCOE) for over 90% of the world [1]. As such, much research, development, and commercial activity are focused on further optimizing this system design for different regions and markets, including field deployment and advanced modeling activities. Despite these efforts, many challenges remain to overcome with this system design. This conference paper will report on several areas the team is working on as part of this project. The first part of this study focuses on extensive interviews with PV tracker companies (we have identified 35) and customers worldwide to identify emerging technology trends, design diversity, market environments, and the reliability and performance of these systems. We will provide a market summary of technologies such as advanced tracking algorithms, methods for dealing with topography within the PV plant, different system configurations and layouts, backside irradiance optimization from albedo enhancement, and ground sculpting. We will also review dual-use applications of tracked bifacial systems, such as Agrivoltaics and Building-Integrated PV. These interviews are underway now, and we will be able to report our initial findings at the conference. The second part of the study focuses on summarizing performance monitoring and evaluation methods, with particular attention to capacity and acceptance testing for such systems. The third part of the study reviews performance modeling and yield assessment methods for these tracked bifacial PV systems. The final part of the study covers reliability and operations, and maintenance data from these systems.

albedo↗