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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Water-soluble saponins accumulate in drought-stressed switchgrass and may inhibit yeast growth during bioethanol production

Abstract Background Developing economically viable pathways to produce renewable energy has become an important research theme in recent years. Lignocellulosic biomass is a promising feedstock that can be converted into second-generation biofuels and bioproducts. Global warming has adversely affected climate change causing many environmental changes that have impacted earth surface temperature and rainfall patterns. Recent research has shown that environmental growth conditions altered the composition of drought-stressed switchgrass and directly influenced the extent of biomass conversion to fuels by completely inhibiting yeast growth during fermentation. Our goal in this project was to find a way to overcome the microbial inhibition and characterize specific compounds that led to this inhibition. Additionally, we also determined if these microbial inhibitors were plant-generated compounds, by-products of the pretreatment process, or a combination of both. Results Switchgrass harvested in drought (2012) and non-drought (2010) years were pretreated using Ammonia Fiber Expansion (AFEX). Untreated and AFEX processed samples were then extracted using solvents (i.e., water, ethanol, and ethyl acetate) to selectively remove potential inhibitory compounds and determine whether pretreatment affects the inhibition. High solids loading enzymatic hydrolysis was performed on all samples, followed by fermentation using engineered Saccharomyces cerevisiae . Fermentation rate, cell growth, sugar consumption, and ethanol production were used to evaluate fermentation performance. We found that water extraction of drought-year switchgrass before AFEX pretreatment reduced the inhibition of yeast fermentation. The extracts were analyzed using liquid chromatography–mass spectrometry (LC–MS) to detect compounds enriched in the extracted fractions. Saponins, a class of plant-generated triterpene or steroidal glycosides, were found to be significantly more abundant in the water extracts from drought-year (inhibitory) switchgrass. The inhibitory nature of the saponins in switchgrass hydrolysate was validated by spiking commercially available saponin standard (protodioscin) in non-inhibitory switchgrass hydrolysate harvested in normal year. Conclusions Adding a water extraction step prior to AFEX-pretreatment of drought-stressed switchgrass effectively overcame inhibition of yeast growth during bioethanol production. Saponins appear to be generated by the plant as a response to drought as they were significantly more abundant in the drought-stressed switchgrass water extracts and may contribute toward yeast inhibition in drought-stressed switchgrass hydrolysates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Thin-film chemical expansion of ceria based solid solutions: laser vibrometry study

The chemical expansion of Pr 0.1 Ce 0.9 O 2-δ (PCO) and CeO 2-δ thin films is investigated in the temperature range between 600 °C and 800 °C by laser Doppler vibrometry (LDV). It enables non-contact determination of nanometer scale changes in film thickness at high temperatures. The present study is the first systematic and detailed investigation of chemical expansion of doped and undoped ceria thin films at temperatures above 650 °C. The thin films were deposited on yttria stabilized zirconia substrates (YSZ), operated as an electrochemical oxygen pump, to periodically adjust the oxygen activity in the films, leading to reversible expansion and contraction of the film. This further leads to stresses in the underlying YSZ substrates, accompanied by bending of the overall devices. Film thickness changes and sample bending are found to reach up to 10 and several hundred nanometers, respectively, at excitation frequencies from 0.1 to 10 Hz and applied voltages from 0–0.75 V for PCO and 0–1 V for ceria. At low frequencies, equilibrium conditions are approached. As a consequence maximum thin-film expansion of PCO is expected due to full reduction of the Pr ions. The lower detection limit for displacements is found to be in the subnanometer range. At 800 °C and an excitation frequency of 1 Hz, the LDV shows a remarkable resolution of 0.3 nm which allows, for example, the characterization of materials with small levels of expansion, such as undoped ceria at high oxygen partial pressure. As the correlation between film expansion and sample bending is obtained through this study, a dimensional change of a free body consisting of the same material can be calculated using the high resolution characteristics of this system. A minimum detectable dimensional change of 5 pm is estimated even under challenging high-temperature conditions at 800 °C opening up opportunities to investigate electro-chemo-mechanical phenomena heretofore impossible to investigate. The expansion data are correlated with previous results on the oxygen nonstoichiometry of PCO thin films, and a defect model for bulk ceria solid solutions is adopted to calculate the cation and anion radii changes in the constrained films during chemical expansion. The constrained films exhibit anisotropic volume expansion with displacements perpendicular to the substrate plane nearly double that of bulk samples. The PCO films used here generate high total displacements of several 100 nm’s with high reproducibility. Consequently, PCO films are identified to be a potential core component of high-temperature actuators. They benefit not only from high displacements at temperatures where most piezoelectric materials no longer operate while exhibiting, low voltage operation and low energy consumption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1976

Airframe technology for energy efficient transport aircraft

NASA has initiated a comprehensive Aircraft Energy Efficiency Program which is concerned with the development of approaches for reducing fuel consumption in new aircraft of the 1980-2000 time period. A review is presented of the airframe technologies selected for emphasis in the NASA program, taking into account an evaluation of their potential for reducing transport direct operating costs through fuel efficiency. Attention is given to the importance of fuel efficiency, the impact of advanced technology, advanced composite structures, the NASA composite primary structures program, advanced aerodynamics and active controls, supercritical wing geometry, active load and flutter control, and aspects of laminar flow control.

Leonard, R. W.↗
NASA NTRS1996

Renal-Stone Risk Assessment During Space Shuttle Flights

The metabolic and environmental factors influencing renal stone formation before, during, and after Space Shuttle flights were assessed. We established the contributing roles of dietary factors in relationship to the urinary risk factors associated with renal stone formation. 24-hr urine samples were collected prior to, during space flight, and following landing. Urinary factors associated with renal stone formation were analyzed and the relative urinary supersaturation ratios of calcium oxalate, calcium phosphate (brushite), sodium urate, struvite and uric acid were calculated. Food and fluid consumption was recorded for a 48-hr period ending with the urine collection. Urinary composition changed during flight to favor the crystallization of stone-forming salts. Factors that contributed to increased potential for stone formation during space flight were significant reductions in urinary pH and increases in urinary calcium. Urinary output and citrate, a potent inhibitor of calcium-containing stones, were slightly reduced during space flight. Dietary intakes were significantly reduced for a number of variables, including fluid, energy, protein, potassium, phosphorus and magnesium. This is the first in-flight characterization of the renal stone forming potential in astronauts. With the examination of urinary components and nutritional factors, it was possible to determine the factors that contributed to increased risk or protected from risk. In spite of the protective components, the negative contributions to renal stone risk predominated and resulted in a urinary environment that favored the supersaturation of stone-forming salts. The importance of the hypercalciuria was noted since renal excretion was high relative to the intake.

Whitson, Peggy A.↗
NASA NTRS2002

Thermodynamic Cycle and CFD Analyses for Hydrogen Fueled Air-breathing Pulse Detonation Engines

This paper presents the results of a thermodynamic cycle analysis of a pulse detonation engine (PDE) using a hydrogen-air mixture at static conditions. The cycle performance results, namely the specific thrust, fuel consumption and impulse are compared to a single cycle CFD analysis for a detonation tube which considers finite rate chemistry. The differences in the impulse values were indicative of the additional performance potential attainable in a PDE.

Povinelli, Louis A.↗
NASA NTRS2009

Distillation and Air Stripping Designs for the Lunar Surface

Air stripping and distillation are two different gravity-based methods, which may be applied to the purification of wastewater on the lunar base. These gravity-based solutions to water processing are robust physical separation techniques, which may be advantageous to many other techniques for their simplicity in design and operation. The two techniques can be used in conjunction with each other to obtain high purity water. The components and feed compositions for modeling waste water streams are presented in conjunction with the Aspen property system for traditional stage distillation models and air stripping models. While the individual components for each of the waste streams will vary naturally within certain bounds, an analog model for waste water processing is suggested based on typical concentration ranges for these components. Target purity levels for the for recycled water are determined for each individual component based on NASA s required maximum contaminant levels for potable water Distillation processes are modeled separately and in tandem with air stripping to demonstrate the potential effectiveness and utility of these methods in recycling wastewater on the Moon. Optimum parameters such as reflux ratio, feed stage location, and processing rates are determined with respect to the power consumption of the process. Multistage distillation is evaluated for components in wastewater to determine the minimum number of stages necessary for each of 65 components in humidity condensate and urine wastewater mixed streams. Components of the wastewater streams are ranked by Henry s Law Constant and the suitability of air stripping in the purification of wastewater in terms of component removal is evaluated. Scaling factors for distillation and air stripping columns are presented to account for the difference in the lunar gravitation environment. Commercially available distillation and air stripping units which are considered suitable for Exploration Life Support are presented. The advantages to the various designs are summarized with respect to water purity levels, power consumption, and processing rates.

Boul, Peter J.↗
NASA NTRS2019

Oculometric Assessment of Mild Neural Impairment

For over 100 years, neurologists have used eye movements to identify neural impairment, disease, or injury. Prior to the age of modern imaging, qualitative assessment of eye movements was a critical, routine component of diagnosis and remains today a routine law-enforcement tool for detecting impaired driving due to drugs or alcohol. We will describe the application of a simple 5-minute oculomotor tracking task coupled with a broad range of quantitative analyses of high-resolution oculomotor measurements for the sensitive detection of sub-clinical neural impairment and for the potential differentiation of various causes. Specifically, we will show that there are distinct patterns of impairment across our set of oculometric parameters observed with brain trauma, sleep and circadian disruption, and alcohol consumption. Such differences could form the basis of a self-administered medical monitoring or diagnostic support tool.

Stone, Lee↗
DOE OSTI2022

Potential State Regulatory Pathways to Facilitate Low-Carbon Fuels

States and the federal government are increasingly engaged in the challenges around decarbonizing the electric grid. In particular, regulators, consumers, stakeholders, and utilities recognize the need to carefully consider the role natural gas will play in a decarbonized future. A variety of technology and policy options to reduce greenhouse gas emissions associated with natural gas use are available, including energy efficiency programs, demand reduction tools, strategic electrification, and strategies to reduce emissions from natural gas production, transportation, and consumption. Low-carbon fuels – mainly renewable natural gas (RNG) and clean hydrogen – are being considered an important component of decarbonization goals. RNG and hydrogen may be able to meaningfully reduce emissions from processes independent of geologic natural gas, displacing emissions of methane, a powerful greenhouse gas. Although RNG and hydrogen are not cost-competitive today with geologic natural gas and are smaller in scale and potential than other decarbonization options, they can be explored as potential critical tools to decarbonize sectors that are difficult to electrify or shift off of natural gas entirely, such as air travel, industrial processes, maritime transport, long-distance trucking, space heating on cold days, and railroads (Nadel, 2022). The role of this report is to provide informational context for state utility regulators to understand the impacts of and challenges associated with broader integration of low-carbon fuels, followed by examples of state regulatory actions taken to date to facilitate the development of low-carbon fuels. Setting clear guidance to calculate the environmental benefits of low-carbon fuels and continuing federal and state investments in research and development to reduce costs relative to fossil fuels will be important steps to take to signal the desire to grow the market for these fuels. State public utility commissions may play a key role in setting regulatory frameworks for low-carbon fuels and ensuring that ratepayer funds, if utilized, are done so to further the public interest. This report is intended to summarize decisions that states have made to date on low-carbon fuels. In the spirit of understanding the current market and sharing information, this report provides success stories, and lessons learned across states as regulators implement varying strategies to achieve decarbonization objectives while maintaining their focus on affordability, safety, and reliability of the energy system. The report begins with an introduction of the role of natural gas in the U.S. economy (Section I) and background information on natural gas use, decarbonization, and low-carbon fuels (Section II). Next, the report describes the current market by discussing the scale of current production, emissions intensity, resource potential, and costs of low-carbon fuels compared to geologic natural gas (Section III). Following these sections, the report describes four strategies states have employed to facilitate low-carbon fuels: opening exploratory dockets, approving voluntary tariffs for customers, approving interconnection tariffs for producers, and considering portfolio-wide procurement targets (Section IV). This section lists states that have taken actions in each category, citing utility filings, commission decisions, stakeholder comments, and other relevant sources. Finally, the report concludes with suggested questions regulators may wish to consider regarding low-carbon fuels, in the interest of preparing to make decisions in the future (Section V). These questions include: Are there existing regulatory or technical barriers to voluntary purchases of low-carbon fuels? Can customers work with utilities to procure low-carbon fuels; are producers able to interconnect projects without significant barriers to entry? Should the infrastructure and/or commodity costs of low-carbon fuels be socialized among all ratepayers, or borne solely by the large commercial and industrial (C&I) customers currently driving the market? Should regulated natural gas and/or electric utilities own and operate low-carbon fuel production? How should regulators consider the unique decarbonization potential of low-carbon fuels, particularly for hard-to-abate sectors, in decision-making? Is additional direction or clarity from state policymakers needed? What no-regrets approaches can help facilitate both near-term RNG development and long-term development of hydrogen and other zero-carbon fuels? We collectively wish to express our gratitude to the U.S. Department of Energy, Office of Fossil Energy and Carbon Management, for supporting this report and other technical assistance resources for state regulators on natural gas topics. State regulators operate under a variety of policy environments, and states have vastly different types of energy resources, infrastructure, and customers. While there is no optimal regulatory, policy, or technological solution that will be successful in every state, state regulators can benefit by exchanging lessons learned with their peers across the country. We look forward to continued engagement with our fellow commissioners, commission staff, NARUC, the U.S. Department of Energy, and other stakeholders to develop sound regulation in the public interest.

03 NATURAL GAS↗
DOE OSTI2026

Validating Simulated Models of Energy Consumption by a Battery Electric Motorcoach: A real-world deployment in a harsh climate.

Many efforts have been made to simulate energy consumption of battery electric buses (BEBs) to optimize their deployment into existing fleets. The models produced, however, are rarely validated against real-world consumption data, limiting their generalizability and widespread application to fleets around the US. Furthermore, a major concern specific to BEBs is the effects of harsh climates on their performance. We build upon the state-of-the-art energy consumption modeling techniques developed for BEBs and apply them to a unique geographic context and a unique electrified vehicle. This geography, climate, and vehicle further the existing understanding of the factors affecting medium- and heavy-duty electric vehicles (MHDEVs) by allowing for new relationships to be tested and by assessing the generalizability of known relationships to new contexts. We find that temperature is less predictive of energy consumption for the battery electric motorcoach (BEM) in the case study environment than it is for BEBs in other studies. A mitigating factor that we presume to be working on the relationship between temperature and energy consumption is the fact that the BEM route does not stop between origin and destination to exchange passengers, and in turn, conditioned cabin air. Our model also incorporates wind speed and direction relative to travel, which is a novel contribution of our methodology. Results from our study are helpful for transit service planners, fleet operators, and logistics firms for improving their ability to predict performance of potential deployments of MHDEVs into existing operations.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗
NASA NTRS1984

Buoyant production and consumption of turbulence kinetic energy in cloud-topped mixed layers

It is pointed out that studies of the entraining planetary boundary layer (PBL) have generally emphasized the role of buoyancy fluxes in driving entrainment. The buoyancy flux is proportional to the rate of conversion of the potential energy of the mean flow into the kinetic energy of the turbulence. It is not unusual for conversion to proceed in both directions simultaneously. This occurs, for instance, in both clear and cloudy convective mixed layers which are capped by inversions. A partitioning of the net conversion into positive parts, generating turbulence kinetic energy (TKE), and negative parts (TKE-consuming), would make it possible to include the positive part in the gross production rate, and closure would be achieved. Three different approaches to partitioning have been proposed. The present investigation is concerned with a comparison of the three partitioning theories. Particular attention is given to the cloud-topped mixed layer because in this case the differences between two partitioning approaches are most apparent.

Randall, D. A.↗
DOE OSTI2020

Chapter 7: Predictive Analytics in Future Power Systems: A Panorama and State-of-the-Art of Deep Learning Applications

The challenges surrounding the optimal operation of power systems are growing in various dimensions, due in part to increasingly distributed energy resources and a progression towards large-scale transportation electrification. Currently, the increasing uncertainties associated with both renewable energy generation and demand are largely being managed by increasing operational reserves - potentially at the cost of suboptimal economic conditions - in order to maintain the reliability of the system. This chapter looks at the big picture role of forecasting in power systems from generation to consumption and provides a comprehensive review of traditional approaches for forecasting generation and load in various contexts. This chapter then takes a deep dive into the state-of-the-art machine learning and deep learning approaches for power systems forecasting. Furthermore, a case study of multi-time-horizon solar irradiance forecasting using deep learning is discussed in detail. Smart grids form the backbone of the future interdependent networks. For addressing the challenges associated with the operations of smart grid, development and wide adoption of machine learning and deep learning algorithms capable of producing better forecasting accuracies is urgently needed. Along with exploring the implementation and benefits of these approaches, this chapter also considers the strengths and limitations of deep learning algorithms for power systems forecasting applications. This chapter, thus, provides a panoramic view of state-of-the-art of predictive analytics in power systems in the context of future smart grid operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Energy-saving potential evaluation for primary schools with occupant-centric controls

Recent studies demonstrated that there is significant energy-saving potential for primary schools, which heating, ventilation, and air-conditioning (HVAC) systems with occupant-centric control (OCC) is an excellent candidate to save energy. However, such an energy impact has yet to be evaluated for different climate zones as well as different energy code versions, but is critical for technology transfer and deployment. Therefore, this paper conducts comprehensive evaluation on the energy-saving potentials for the primary schools with two advanced OCC strategies: presence-based and counting-based. In this work, ninety-six building energy models with stochastic behavior of occupants are developed and simulated, which consist of two building energy code versions, 16 climate zones, and baseline case (without OCC) and two advanced cases (with OCC). To evaluate the energy saving potentials for OCC, primary schools in the U.S. are used as an example. The results show that there is significant energy-saving potential for primary schools by considering OCC strategies, especially the counting-based case. The energy-saving potential is up to 10.2% for presence-based OCC and 12.41% for counting-based OCC. Furthermore, both climate and code version have a significant impact on energy savings from OCC strategies. The energy-saving potentials vary from 1.79% to 12.41% for different climates and code versions. This evaluation can also contribute to quantify the nationwide energy saving potential for other countries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Beyond Energy Efficiency: A clustering approach to embed demand flexibility into building energy benchmarking

The intermittency of carbon-free renewables and the demand changes associated with the widespread push for electrifying the transportation and building sectors provides an opportunity for buildings to go beyond energy efficiency and push towards providing demand flexibility to the electricity grid. The duality of energy efficiency and demand flexibility is necessary for success in a sustainable and reliable energy transition. Current building energy benchmarking models are limited in their ability to integrate concepts of demand flexibility and/or utilize granular smart meter data. Thus, current benchmarking methods are focused annual energy usage and fail to incorporate how the time of use of energy consumption impacts emissions in a quickly changing energy grid. Without a more comprehensive view of energy usage and associated real-time emissions, current benchmarking methods are unlikely to realize the full decarbonization potential of buildings. New emerging data streams provide an opportunity to develop a new generation of benchmarking energy models that embed dimensions of energy efficiency, grid interactivity, and demand flexibility into their analysis. In this paper, we propose a four-step method for embedding grid interactivity and demand flexibility into building benchmarking models that utilizes emerging building and time-series electricity data streams. We first engineer features to produce a mix-type dataset that encompasses many attributes of grid-interactive and efficient buildings, and then we apply K-medoids using Gower's Distance to produce peer-group clusters. We apply the method to a case study of 306 primary and secondary schools in southern California, USA. The results show that the method effectively clusters buildings by attributes of demand flexibility and energy efficiency. The clustering results reveal patterns in inefficient building operations and demand inflexibility at the building peer group level. In conclusion, the interpretation of clusters can serve as an integrated energy efficiency and demand flexibility benchmarking model and inform performance-specific policy targeting for buildings that go beyond traditional efficiency measures.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Model predictive control of heating, ventilation, and air conditioning (HVAC) systems: A state-of-the-art review

Due to the fast advancement of communication and information technology, intelligent buildings have garnered great interest. These buildings can forecast weather, ambient temperature, and sun irradiation and can modify heating, ventilation, and air conditioning (HVAC) operations appropriately, based on current and previous data. This change is intended to reduce HVAC system energy usage while maintaining an appropriate degree of thermal comfort and indoor air quality. Since its inception, model predictive control (MPC) has been one of the prospective solutions for HVAC management systems to reduce both costs and energy usage. Additionally, MPC is becoming increasingly practical as the processing capacity of building automation systems increases and a large quantity of monitored building data becomes available. MPC also provides the potential to improve the energy efficiency of HVAC systems via its capacity to consider limitations, to predict disruptions, and to factor in multiple competing goals such as interior thermal comfort and building energy consumption. Although substantial research has been conducted on MPC in building HVAC systems, there is a shortage of critical reviews and a lack of a comprehensive framework that formulates and defines the applications. Here, this article provides a comprehensive state-of-the-art overview of MPC in HVAC systems. Detailed discussions of modeling approaches and optimization algorithms are included. Numerous design aspects such as prediction horizon, occupancy behavior, building type, and cost function, that impact MPC performance are discussed in detail. The technical characteristics, advantages, and disadvantages of various types of modeling software are discussed. The primary objective of this work is to highlight critical design characteristics for the MPC control scheme and to give improved suggestions for future research. Moreover, numerous prospective scenarios have been suggested that might provide future research direction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Enhancing Nitrogen Activation in Electrochemical Reduction: The Role of Rare Earth Oxide Surface Configurations

The pursuit of sustainable ammonia synthesis has prompted the exploration of ambient electrochemical nitrogen reduction reaction (e-NRR) as an alternative to the energy-intensive Haber-Bosch process. Here, this study conducted a theoretical investigation into the use of rare earth oxide materials, specifically dysprosium oxide (Dy 2 O 3 ), as potential electrocatalysts for NRR. Utilizing spin-polarized density functional theory calculations, we explored the interaction between Dy 2 O 3 surfaces and nitrogen (N 2 ) molecules, examining the capability of Dy 2 O 3 to adsorb and activate N 2 under ambient conditions. The results indicate that Dy 2 O 3 surfaces exhibit diverse configurations and bonding environments, providing a variety of reactive sites that display different behaviors in N 2 adsorption and activation. The distinctive electronic structure and surface chemistry of a particular Dy 2 O 3 surface configuration were found to significantly enhance the activation of N 2 by promoting charge transfer, which facilitates the NRR process. This research provides deep insights into the mechanistic pathways of N 2 reduction over Dy 2 O 3 , highlighting the surface properties as pivotal in catalysis. These theoretical insights serve as a foundation for the development of novel rare earth-based electrocatalytic materials for efficient ambient e-NRR, potentially transforming ammonia production into a greener and more energy-efficient process.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

ChemComp: A Compilation Framework for Computing with Chemical Reaction Networks

The acceleration of scientific computation, data analytics, and artificial intelligence is driving a surge in computational requirements. Yet, state-of-the-art high-performance computing systems are approaching physical limitations that impede further significant improvements in energy efficiency. As we move towards post-exascale computing systems, innovative approaches are necessary to overcome this barrier in power consumption. Novel analog and hybrid digital-analog architectures hold promise for enhancing energy efficiency by several orders of magnitude. Biochemical computation stands out among the various solutions being explored due to its potential to enable new classes of devices with immense computational capabilities. These devices can capitalize on the inherent efficacy of biological cells in solving optimization problems and are scalable through increasing reaction system size or vessel capacity, potentially satisfying scientific computing's high-performance requirements. Nonetheless, several theoretical and practical limitations persist, including problem formulation and mapping to chemical reaction networks (CRNs) and implementation of actual CRN devices. In this paper, we propose a framework for biochemical computation using systems chemistry. We present the initial components of our approach: an abstract chemical reaction dialect implemented as a multi-level intermediate representation (MLIR) compiler extension and a pathway to represent mathematical problems with CRNs. To showcase the potential of this approach, we emulate a simplified chemical reservoir device. This work lays the groundwork for leveraging chemistry's computing potential in creating energy-efficient, high-performance computing systems tailored to contemporary computational needs.

artificial intelligence↗
DOE OSTI2020

Review: Sensor Impact on Building Controls and Automatic Fault Detection and Diagnosis (AFDD)

This report summarizes a literature review as a Q1 deliverable of the “Sensor Impact Evaluation and Verification” project. This project’s overarching goal is to develop a framework for investigating the impact of sensor deployment and configuration for building energy optimization, fault detection and diagnosis (FDD), occupants’ thermal comfort, and potential grid efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1977

Energy resources of the developing countries and some priority markets for the use of solar energy

Energy consumption for the developed and non-developed world is expressed as a function of GNP. An almost straight-line graph results when energy consumption statistics are treated in this manner. The richest countries consume the most energy, and the poorest countries the least. It therefore follows that greater energy production in the developing countries (leading to greater energy consumption) will contribute to their economic growth. Energy resources in the developing countries are compared, including: solid fossil fuels, crude oil, natural gas, oil shale, and uranium. Mention is also made of the potential of renewable energy resources, such as solar, wind, and hydroelectric power, in the underdeveloped world; and it is these resources which offer the greatest possibilities for economic improvement if the money is forthcoming, i.e., from the world bank, to fund the necessary technology.

Siddiqi, T. A.↗