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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Low-energy particle population

A review is conducted of the measurements of the intensities, energy spectra, angular variations, and composition characteristics of the low-energy ion population in and around the Jovian magnetosphere, taking into account data obtained by both Voyager spacecraft. A description is provided of some novel analysis techniques which have been employed to generate density, pressure, composition, and plasma flow profiles in the magnetosphere. The obtained results are compared with data reported in connection with other investigations related to the spacecraft. Attention is given to the Low-Energy Charged Particle investigation, the Voyager 1 and 2 trajectories within 1000 Jupiter radii, and a hot plasma model of the Jovian magnetosphere. The measurement of hot multispecies convected plasmas using energetic particle detectors is also discussed.

Krimigis, S. M.↗
NASA NTRS1981

Spectral and compositional variations of low energy ions during an energetic storm particle event

Attention is given to variations in the intensity, energy spectra, and composition of low-energy protons, helium, and heavy ions (C, O, and Fe) in the energy range 0.3-20 MeV per nucleon during an energetic storm particle event on September 28-29, 1978. The intensities of low enery (less than or equal to 0.6 MeV per nucleon) particles are found to increase exponentially with time before the arrival of the moving interplanetary shock front. The increase is largest for the particles of lowest energy. The spectral steepening, expressed in terms of differences in the spectral index, increases for particles of increasing mass per charge ratio from a difference of approximately 1 for protons to approximately 3 for iron. As a consequence, the He/O and C/O ratios at equal energy per nucleon are constant, whereas the He/p, Fe/He, and Fe/O ratios decrease by as much as one order of magnitude before passage of the shock. The observations are analyzed in terms of a first-order Fermi acceleration model with a rigidity dependent interplanetary mean free path.

Klecker, B.↗
DOE OSTI2022

A machine learning approach for clinker quality prediction and nonlinear model predictive control design for a rotary cement kiln

Abstract Cement manufacturing is energy‐intensive (5Gj/t) and comprises a significant portion of the energy footprint of concrete systems. Incorporating modern monitoring, simulation and control systems will allow lower energy use, lower environmental impact, and lower costs of this widely used construction material. One of the goals of the CESMII roadmap project on the Smart Manufacturing of Cement included developing an analytical process model for clinker quality that includes the chemistry of the kiln feed and accounts for critical process variables. This predictive model will be used in nonlinear model predictive control system designed to significantly reduce process energy use while maintaining or improving product quality. In the cement manufacturing plant used in this study, the kiln feed (meal) is tested every 12 h and used to estimate the mineral composition of the cement kiln output (clinker) using the stoichiometry‐based Bogue's model and the expertise of the plant operators. During kiln operation, kiln output (clinker) is sampled and tested every 2 h to measure its chemical and mineral composition. The predicted and measured values of the clinker composition are used by the plant operators to adjust the kiln input stream and the production process characteristics to maintain stable operation and uniform product quality. However, the time delay between prediction and testing, along with inaccuracies inherent in the Bogue's model have made any process changes designed to minimize energy use problematic, especially in‐light of potential clinker quality issues that process changes often pose. A new analytical model that integrates quality information and process operation information has been developed from data collected from 2 years of production from an operating cement facility. To make the model fuel‐type‐independent, consumed heat energy was computed in the model instead of fuel type and amount. A Feedforward Network was trained and tailored from collected data. Many data‐based simulations were conducted to quantitatively evaluate the proposed model and the 5‐fold cross‐validation procedure was used to test the models. The resulting predictive model was shown to have a low root mean square error (MSE) with respect to the estimated clinker mineral composition compared to that using the industry standard “Bogue’ model”. The end goal of this work was to develop a single machine learning tool that allows the use of quality control data and process control variables to improve energy efficiency of the process in a continuous fashion. The proposed nonlinear model predictive control system (NMPC) can generate predicted kiln production characteristics based on manipulated variables in manner that accurately follows the target product quality values. Simulation results also show that the proposed model produced accurate predictions of kiln outputs that fell within the required constraints, while manipulating control variables within typical operational ranges.

Ali, Asem M.↗
DOE OSTI2024

Dual-module humidity pump for efficient air dehumidification: Demonstration and performance limitations

Condensation dehumidification in conventional air conditioning technologies is energy-intensive, accounting for up to 50% of building cooling energy used in some climates. Selective vacuum membrane dehumidification (VMD) is one of the leading alternative dehumidification technologies due to its potential for significant energy savings, and the “dual-module humidity pump” is one of the most promising VMD concepts. Here, this work is the first to provide experimental proof-of-concept for the dual-module humidity pump system and provides the first thermodynamic modeling framework that accounts for realistic steady-state operating limitations, both of which are lacking in the current literature. Additionally, this work is the first to provide a system design solution that overcomes practical challenges associated with air accumulation in the vacuum channels. The experimental results in this work show that the current prototype can remove up to 45% of the water vapor in the air stream, and the vapor pressure difference in the vapor rejection module needs to be approximately 2–4 times greater than that of the dehumidification module in order to maintain balanced mass transfer. The thermodynamic model applied to typical air conditioning conditions shows that the ideal dehumidification (latent) COPs can reach up to 40, but practical COPs are limited to approximately 10. Furthermore, the model shows that the overall energy efficiency increases as the membrane air selectivity increases, though this improvement gradually starts to diminish when the membrane selectivity is increased above 10,000.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Low Energy Ultrasonic Separation

Separations exist in all manufacturing sectors, accounting for 22% of in-plant energy use. Whereas energy-intense technologies such as centrifuges are well established, low energy separations account for only 1% of industrial energy consumption. Researchers at Los Alamos National Lab are developing a low energy ultrasonic particle concentrator for industry. This technology may reduce energy use, improve separations, reduce wastes, and cut manufacturing costs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Evaluate the System-Level Impact of Connected and Automated Vehicles Coupled with Shared Mobility: An Agent-based Simulation Approach

With the rapid growth of information and communication technologies, Connected and Automated Vehicles (CAVs) are deemed to be disruptive with the potential to significantly improve overall transportation system efficiency, however, may bring Vehicle Miles Traveled (VMT) increase or other issues. Further, shared mobility systems are another disruptive force that is reshaping our travel patterns. To quantify the combined impact of CAV and shared mobility on travel behavior, traffic performance and energy efficiency, we develop a mesoscopic simulation-based framework for mobility and energy efficiency evaluation considering the disruptive transportation technologies. Under this framework, we develop novel models for energy intensity and modal activity, and evaluated a variety of energy scenarios for different combinations of CAV applications, various levels of automation, roadway characteristics, and traffic conditions, while also varying different vehicle types and fuel/powertrain technologies. Based applying this modeling suite to a calibrated BEAM simulation network in Riverside California, it was found that cooperative automated driving in general will improve mobility, but automated vehicles, even when deployed in a shared autonomous fleet, will likely bring an increase of VMT (up to 36%) due to mode shifts and deadheading. Ride-hailing vehicles typically have better energy efficiency and a higher share of electric vehicles, which helps offset the negative impact from VMT increases when estimating the system-level energy consumption. In general, simulation results show a 6% increase in energy consumption for the scenarios with an increasing shift to ride-hailing modes.

42 ENGINEERING↗
DOE OSTI2025

Extraction of Terpenoids from Pine Needle Biomass Using Dimethyl Ether

Pine needles are an industrial feedstock for extracts used in a variety of applications, but conventional extraction methods often result in a degradation of the terpenoid compounds that naturally occur in loblolly pine ( Pinus taeda ). Separation of these compounds from pine biomass is an energy-intensive operation, typically requiring a significant input of thermal energy. An alternative separation approach with potential energy savings is extraction with a condensable gas, namely, dimethyl ether. Biomass materials are exposed to liquid dimethyl ether under pressure, which mobilizes the organics. The extract is then separated from the insoluble pine matter, and dimethyl ether is volatilized away from the separated organic species. A variety of terpene derivatives were extracted from pine needle biomass using this approach, including monoterpenes, sesquiterpenes, and related oxygenates, which were identified using two-dimensional gas chromatography/mass spectrometry. Additionally, the dimethyl ether-treated needles resemble needles subjected to low-temperature drying, whereas needles treated with a high-temperature drying method appear to have shrunken structures. The results suggest that dimethyl ether extraction has significant potential for separating valuable organics from complex matrices without the application of thermal energy during treatment.

dimethyl ether (DME) extraction↗
NASA NTRS1982

An assessment of gas-side fouling in cement plants

The cement industry is the most energy-intensive industry in the United States in terms of energy cost as a percentage of the total product cost. An assessment of gas-side fouling in cement plants with special emphasis on heat recovery applications is provided. In the present context, fouling is defined as the buildup of scale on a heat-transfer surface which retards the transfer of heat and includes the related problems of erosion and corrosion. Exhaust gases in the cement industry which are suitable for heat recovery range in temperature from about 100 to 1300 K, are generally dusty, may be highly abrasive, and are often heavily laden with alkalies, sulfates, and chlorides. Particulates in the exhaust streams range in size from molecular to about 100 micrometers in diameter and come from both the raw feed as well as the ash in the coal which is the primary fuel used in the cement industry. The major types of heat-transfer equipment used in the cement industry include preheaters, gas-to-air heat exchangers, waste heat boilers, and clinker coolers. At the present time, the trend in this country is toward suspension preheater systems, in which the raw feed is heated by direct contact with the hot kiln exit gases, and away from waste heat boilers as the principal method of heat recovery. The most important gas-side fouling mechanisms in the cement industry are those due to particulate, chemical reaction, and corrosion fouling.

Marner, W. J.↗
NASA NTRS2008

Energy and Mass Transport of Magnetospheric Plasmas during the November 2003 Magnetic Storm

Intensive energy and mass transport from the solar wind across the magnetosphere boundary is a trigger of magnetic storms. The storm on 20-21 November 2003 was elicited by a high-speed solar wind and strong southward component of interplanetary magnetic field. This storm attained a minimum Dst of -422 nT. During the storm, some of the solar wind particles enter the magnetosphere and eventually become part of the ring current. At the same time, the fierce solar wind powers strong outflow of H+ and O+ from the ionosphere, as well as from the plasmasphere. We examine the contribution of plasmas from the solar wind, ionosphere and plasmasphere to the storm-time ring current. Our simulation shows, for this particular storm, ionospheric O+ and solar wind ions are the major sources of the ring current particles. The polar wind and plasmaspheric H+ have only minor impacts. In the storm main phase, the strong penetration of solar wind electric field pushes ions from the geosynchronous orbit to L shells of 2 and below. Ring current is greatly intensified during the earthward transport and produces a large magnetic depression in the surface field. When the convection subsides, the deep penetrating ions experience strong charge exchange loss, causing rapid decay of the ring current and fast initial storm recovery. Our simulation reproduces very well the storm development indicated by the Dst index.

Fok, Mei-Chging↗
NASA NTRS1965

Low energy trapped protons and electrons.

Explorer satellite XII, XIV and XV MEASUREMENTS, noting directional intensity energy flux, spatial distribution and spectra of low energy trapped protons and electrons

EXPLORER XII SATELLITE↗
DOE OSTI2020

The global energy footprint of information and communication technology electronics in connected Internet-of-Things devices

Information and communication technology (ICT) has been critical to the emergence of a new Internet-of-Things (IoT) era, as a rapidly increasing number and variety of IoT electronic devices in a wide range of end-use sectors require massive data communication in terms of volume, velocity/speed, and variety. Additionally, semiconductor technology advancements have played a key role in ICT and unlike the past ICT energy footprint analysis, which focused on the final electronic product, an attempt has been made to examine the global energy impacts for the period 2016–2025 based on the market forecasts of three major IoT IC types, i.e., sensors and actuators, connectivity, and processor ICs distributed among four major IoT device components.Total global IoT semiconductor primary energy demand is projected to increase from 2 EJ in 2016 to 35 EJ by 2025, resulting mainly from a substantial projected increase energy needed in the manufacturing of ICs, with growth in the use of sensors and energy-intensive next fab generation manufacturing. Unlike the trend in manufacturing energy, total global operational energy use is projected to decrease significantly with the development of smaller transistor size, low-power devices, and faster wireless data communication technology. Total operational energy is projected to significantly decrease from 118 TWh/year (1,2 EJ/year) to less than 1 TWh/year (0.003 EJ/year) in spite of a significantly higher anticipated growth in its market size during the 2016–2025 forecast period. Its annual share of total primary energy use is projected to reach an insignificant level of 0.01% by the end of 2025, consistent with the past limited electronic product life cycle analyses besides the analysis focus here limited to ICs in IoT devices.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Study of Ion Generation by a ps-laser for External Injection into Electron Beam Ion Source

We investigated ion generation from Al, Ti, Cu, Nb and Ta target elements by a picosecond-laser in the range of 10 11 – 10 13 W/cm 2 power densities at the target surface. A ps-laser with 1.27 mJ maximum energy within a 8 ps pulse and repetition rate up to 400 Hz has been used to generate a laser-ablated plasma. Dependencies of ion current vs time, total charge of registered ions as well as ion kinetic energy distributions are characterized using a Faraday cup. Significant difference in ion current dynamics between first, second and following shots onto the same target spot was found for all five target elements. The total charge of ions registered by the Faraday cup increase linearly with increasing laser pulse energy and are almost independent on the target element and number of shots onto the same target spot for all five target elements studied. Target craters have been examined using a commercially available microscope (Nikon Eclipse LV150) and crater cross section areas were found to be in the range of 0.0076 – 0.0172 mm 2 within the first five shots onto the same target spot for different target elements. A linear dependence of crater cross section square on laser pulse energy has been observed for the Ta target. Ion energy distributions for all target elements have a plateau or a slight peak in the energy range of 10 - 100 eV and long low-intensity energy tail up to tens of keV.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Initial Findings from US Department of Energy’s Better Plants Virtual in-Plant Training on 50001 Ready

Manufacturing facilities use about 35% of the domestic energy in the United States every year. Implementing an effective energy management system (EnMS) is one of the most important approaches to improve energy efficiency. However, the implementation of EnMS is low for many countries (including the US) and even for energy-intensive sectors. The reasons for the low implementation rate of energy management systems had been investigated by multiple researchers, but very few studies have focused on the barriers and challenges of implementing ISO 50001-based energy management systems. To contribute to this understudied area, this paper discusses the implementation and outcomes of the first Better Plants 50001 Ready Virtual In-plant Training. This paper first provides an overview of 50001 Ready and the 50001 Ready Navigator Tool. Then, it provides details on this training event and its outcomes. Finally, it discusses findings from the responses to 40 live polling questions about the status of the 25 tasks of the 50001 Ready Navigator for participating companies, key components of the participating manufacturing companies’ energy management systems, and challenges and barriers that these companies are facing. The findings suggest that although many companies understood the importance of an effective energy management system, about half of them do not understand the required resources for building energy management systems, and most of them have only just begun establishing these systems and need more assistance and resources in multiple areas. More specifically, more assistance is necessary for the following: (1) improving corporate management’s understanding of the time and resources needed to build an EnMS as well as the benefits; (2) creating linear regression models for more accurate energy performance tracking; (3) understanding energy use, collecting and analyzing energy performance data; (4) optimizing equipment operational controls, and creating action plans.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Process Heating Assessments Using DOE’s Manufacturing Energy Assessment Software for Utility Reduction (MEASUR) Tool Suite

Process heating is the most energy-intensive manufacturing process for most sectors of industry. To quantify energy savings from various energy conservation measures, the Department of Energy (DOE) sponsored the development of the Process Heating Assessment and Survey Tool (PHAST) and similar tools for other industrial systems in the early 2000s. It has been used extensively in the Save Energy Now Program’s Energy Savings Assessments and the Better Plants Program’s In-Plant Trainings. Since the initial development of the legacy tools, both computer operating systems and software development have evolved significantly. Thus, DOE has invested in the modernization of PHAST and other legacy software tools to create the Manufacturing Energy Assessment Software for Utility Reduction (MEASUR) tool suite. MEASUR offers a collection of software tools that can aid manufacturing facilities in improving the efficiency of energy systems and equipment (specifically pumps, fans, steam, and process heating) and in conducting “Energy Treasure Hunts”. Eventually, the tool will also add compressed air and process cooling systems. The Process Heating Assessment (PHA) module of MEASUR is an upgrade of the PHAST tool. PHA provides the means to model fuel-fired, steam-based, and electric process heating systems, covering process heating for most industrial plants in manufacturing sector. It also includes several key upgrades, including the ability to consider multi-component charge loads and account for several different areas of energy losses. The new tool includes a comprehensive flue gas calculator to quantify available heat and heat loss for various gaseous, liquid, and solid fuels and new heat loss calculators. It generates a report and a dynamic Sankey diagram to show the energy consumption in various areas of energy use. MEASUR has significantly improved the user experience by adopting a modern software design. This paper details the structure and workflow of PHA and presents a real-world case study to demonstrate energy savings quantification and MEASUR’s outstanding reporting capabilities.

Nimbalkar, Sachin U.↗
DOE OSTI2020

Performance Analysis of a Membrane-based Ionic Liquid Desiccant (ILD) Dehumidifier

Air dehumidification through cooling is an energy-intensive process, which consumes about 20-40% of the overall energy for air-conditioning. Liquid desiccant dehumidification can separate dehumidification from space cooling and has potential to improve the cooling efficiency and reduce the overall energy consumption for air-conditioning. However, the drawbacks such as liquid carryover and corrosion, membrane contamination and blocking, limit its application. To eliminate these problems, a new dehumidifier using nonporous membrane and ionic liquid desiccant (ILD) was developed. The dehumidification performance of the new dehumidifier was characterized through a series of lab tests. Test results indicate that the new dehumidifier can achieve a moisture removal rate up to 180.3 g/h and a dehumidification effectiveness up to 12.7%. A parametric study found that the dehumidification performance is sensitive to the flowrates of the air and the ILD solution. A higher mass flow ratio between the ILD solution and the air could result in better dehumidification performance.

Wang, Lingshi↗
DOE OSTI2024

Towards Energy–Efficient Direct Air Capture with Photochemically–Driven CO 2 Release and Solvent Regeneration

The intensive energy demands associated with solvent regeneration and CO 2 release in current direct air capture (DAC) technologies makes their deployment at the massive scales (GtCO 2 /year) required to positively impact the climate economically unfeasible. This challenge underscores the critical need to develop new DAC processes with significantly reduced energy costs. Recently, we developed a new approach to photochemically drive efficient release of CO 2 through an intermolecular proton transfer reaction by exploiting the unique properties of an indazole metastable-state photoacid (mPAH), opening a new avenue towards energy efficient on-demand CO 2 release and solvent regeneration using abundant solar energy instead of heat. In this Concept Article, we will describe the principle of our photochemically-driven CO 2 release approach for solvent-based DAC systems, discuss the essential prerequisites and conditions to realize this cyclable CO 2 release chemistry under ambient conditions. We outline the key findings of our approach, discuss the latest developments from other research laboratories, detail approaches used to monitor DAC systems in situ, and highlight experimental procedures for validating its feasibility. Finally, we conclude with a summary and outlook into the immediate challenges that must be addressed in order to fully exploit this novel photochemically-driven approach to DAC solvent regeneration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Energy Efficient Material Processing through Automated Process Monitoring and Controls

Smart manufacturing is bound to play a crucial role in reducing global energy consumption while accelerating economic development. This phenomenon is evident in advanced sensing technology developments, data analytics and machine learning/AI, automated controls, cloud computing, etc. The immediate opportunity for smart manufacturing is to improve the energy efficiency of manufacturing operations through innovations in processes and controls. The manufacturing industry still consumes about 30% of total global energy production, which is significant. This program focused on the recommendation of heterogeneous sensors to monitor the Chemical Vapor Infiltration (CVI) process parameters, states, and key performance indices and utilize cloud computing to sort and analyze the real-time data. Learning through data analytics helps guide the control parameters affecting energy usage. The target process in the program is the CVI process at the Honeywell South Bend facility, which is one of the most energy-intensive manufacturing industries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗