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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Status and perspectives of municipal solid waste incineration in China: A comparison with developed regions

Highlights: • Questions about the applicability, technical status, and future of MSW incineration in China are answered. • Comparison involves China, EU, U.S., Japan, South Korea, and Taiwan area. • MSW incineration is not out of date around the world. • The structure of MSW incineration technologies is changing in China. • Perspectives and suggestions are given for the compliance with the emission standard. - Abstract: With the rapid expansion of municipal solid waste (MSW) incineration, the applicability, technical status, and future improvement of MSW incineration attract much attention in China. This paper aims to be a sensible response, with the aid of a comparison between China and some representative developed regions including the EU, the U.S., Japan, South Korea, and Taiwan area. A large number of up-to-date data and information are collected to quantitatively and impartially support the comparison, which covers a wider range of key points including spatial distribution, temporal evolution, technologies, emissions, and perspectives. Analysis results show that MSW incineration is not an outdated choice; however, policy making should prevent the potentially insufficient utilization of MSW incinerators. The structure of MSW incineration technologies is changing in China. The ratio of plants using fluidized bed is decreasing due to various realistic reasons. Decision-makers would select suitable combustion technologies by comprehensive assessments, rather than just by costs. Air pollution control systems are improved with the implementation of China’s new emission standard. However, MSW incineration in China is currently blamed for substandard emissions. The reasons include the particular elemental compositions of Chinese MSW, the lack of operating experience, deficient fund for compliance with the emission standard, and the lack of reliable supervisory measures. Some perspectives and suggestions from both technical and managerial aspects are given for the compliance with the emission standard. This paper can provide strategic enlightenments for MSW management in China and other developing countries.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Predictive modeling of battery degradation and greenhouse gas emissions from U.S. state-level electric vehicle operation

Electric vehicles (EVs) are widely promoted as clean alternatives to conventional vehicles for reducing greenhouse gas (GHG) emissions from ground transportation. However, the battery undergoes a sophisticated degradation process during EV operations and its effects on EV energy consumption and GHG emissions are unknown. Here we show on a typical 24 kWh lithium-manganese-oxide–graphite battery pack that the degradation of EV battery can be mathematically modeled to predict battery life and to study its effects on energy consumption and GHG emissions from EV operations. We found that under US state-level average driving conditions, the battery life is ranging between 5.2 years in Florida and 13.3 years in Alaska under 30% battery degradation limit. The battery degradation will cause a 11.5–16.2% increase in energy consumption and GHG emissions per km driven at 30% capacity loss. This study provides a robust analytical approach and results for supporting policy making in prioritizing EV deployment in the U.S.

Science & Technology - Other Topics↗
DOE OSTI2023

Muted extratropical low cloud seasonal cycle is closely linked to underestimated climate sensitivity in models

Abstract A large spread in model estimates of the equilibrium climate sensitivity (ECS), defined as the global mean near-surface air-temperature increase following a doubling of atmospheric CO 2 concentration, leaves us greatly disadvantaged in guiding policy-making for climate change adaptation and mitigation. In this study, we show that the projected ECS in the latest generation of climate models is highly related to seasonal variations of extratropical low-cloud fraction (LCF) in historical simulations. Marked reduction of extratropical LCF from winter to summer is found in models with ECS > 4.75 K, in accordance with the significant reduction of extratropical LCF under a warming climate in these models. In contrast, a pronounced seasonal cycle of extratropical LCF, as supported by satellite observations, is largely absent in models with ECS < 3.3 K. The distinct seasonality in extratropical LCF in climate models is ascribed to their different prevailing cloud regimes governing the extratropical LCF variability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Case study on climate change effects and food security in Southeast Asia

Agriculture, a cornerstone of human civilization, faces rising challenges from climate change, resource limitations, and stagnating yields. Precise crop production forecasts are crucial for shaping trade policies, development strategies, and humanitarian initiatives. This study introduces a comprehensive machine learning framework designed to predict crop production. We leverage CMIP5 climate projections under a moderate carbon emission scenario to evaluate the future suitability of agricultural lands and incorporate climatic data, historical agricultural trends, and fertilizer usage to project yield changes. Our integrated approach forecasts significant regional variations in crop production across Southeast Asia by 2028, identifying potential cropland utilization. Specifically, the cropland area in Indonesia, Malaysia, Philippines, and Viet Nam is projected to decline by more than 10% if no action is taken, and there is potential to mitigate that loss. Moreover, rice production is projected to decline by 19% in Viet Nam and 7% in Thailand, while the Philippines may see a 5% increase compared to 2021 levels. Our findings underscore the critical impacts of climate change and human activities on agricultural productivity, offering essential insights for policy-making and fostering international cooperation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

21st Century United States Emissions Mitigation Could Increase Water Stress more than the Climate Change it is Mitigating

By using coupled models of human and earth system processes, we show that climate mitigation would result in an increase in the total magnitude and spatial extent of surface water deficits for almost all U.S. water resources regions, and in larger and more extreme hotspots of water deficits—primarily due to the increased demand for bioenergy crops. Most water deficits will be experienced by the agricultural sector, with the exception of Northeast region of the US. In addition, using models capable of resolving higher spatial and temporal variability and representing human-earth system interactions, we reveal that climate mitigation may have large human footprints on streamflows, especially in dry regions. This research shows the potential for unintended and negative consequences of climate mitigation if human-natural system interactions are ignored in policy-making.

mitigation, Integrated assessment model, Earth sys↗
DOE OSTI2021

Advancing a toolkit of diverse futures approaches for global environmental assessments

Global Environmental Assessments (GEAs) support national and international policy making for sustainable development. They rely on quantitative scenarios produced by Integrated Assessment Models (IAMs) to assess alternative futures. IAM-based scenarios can provide a coherent assessment framework that integrates different subsystems and their interactions. However, these top-down approaches have limited ability to represent key local dynamics, unexpected events, or the role of diverse actors. Other methods, including participatory scenarios, can help co-create narratives that emphasize diverse contents with clear links to existing decision-making. However, these bottom-up approaches provide only limited insight into global processes and are not constrained by measurable parameters. In our review, we identify four key challenges for current GEA scenarios: surprise, scale, diversity and imagination. We illustrate how these challenges can be overcome by combining top-down and bottom-up scenario approaches and conclude with a call to action for future research to take on this trans-disciplinary challenge.

Pereira, Laura M.↗
DOE OSTI2023

Understanding uncertainties in projections of western North Pacific tropical cyclogenesis

Reliable projections of tropical cyclone (TC) activities in the western North Pacific (WNP) are crucial for climate policy-making in densely-populated coastal Asia. Existing projections, however, exhibit considerable uncertainties with unclear sources. Here, based on future projections by the latest Coupled Model Intercomparison Project Phase 6 climate models, we identify a new and prevailing source of uncertainty arising from different TC identification schemes. Notable differences in projections of detected TCs and empirical genesis potential indices are found to be caused by inconsistent changes in dynamic and thermodynamic environmental factors affecting TC formations. While model uncertainty holds the secondary importance, we show large potential in reducing it through improved model simulations of present-day TC characteristics. Internal variability noticeably impacts near-term projections of the WNP tropical cyclogenesis, while the relative contribution of scenario uncertainty remains small. Our findings provide valuable insights into model development and TC projections, thereby aiding in adaptation decisions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Bias Correction in Urban Building Energy Modeling for Chicago Using Machine Learning

Urban-scale building energy modeling (UBEM) holds promise for optimizing energy usage across extensive geographic regions. However, there is a recognized bias between simulated energy consumption and actual measured data. This study, based on building data from Chicago, delved into bias correction techniques for enhancing the accuracy of UBEM energy consumption estimates. Initially, the AutoBEM simulation yielded a normalized mean bias error (NMBE) of 1.1% and 51% of Coefficient of the Variation of the Root Mean Square Error (CVRMSE) after outlier exclusion. To address this, three bias correction methods were deployed: Average Mean Bias Error based bias correction, Quantile mapping bias correction, and Machine learning-based bias correction using Linear Regression and Random Forest models. Post-correction results exhibited marked improvement. The NMBE values were diminished to 0 for Average MBE-based, 0.36 for Quantile Mapping, and 0 for Machine Learning-based corrections. Concurrently, the CVRMSE values registered reductions from an original 51 to 50.8 for Quantile Mapping, and 38.56 for Machine Learning-based corrections, pointing towards the effectiveness of specific bias correction methods in refining the precision of UBEM energy predictions. Such accurate estimations are paramount for informed energy planning and urban policy-making.

Chowdhury, Shovan↗
DOE OSTI2024

Transmission Interface Limits for High-Spatial Resolution Capacity Expansion Modeling

Large-scale capacity expansion models typically rely on estimates of the power transfer limits between modeled zones. Accurate estimation of these interface transfer limits (ITLs) requires modeling the underlying transmission network. Here we expand on a maximum flow optimization method that uses linearized power flow to estimate transfer limits. We apply this method to a data set of the U.S. transmission network to estimate ITLs between U.S. counties. By calculating ITLs using different subsets of the network, we evaluate how the size of the network used in the estimation affects the results. The results show diminishing returns to ITL accuracy after six hops, suggesting that a network subset can reasonably be used to approximate ITLs. The county-level estimates produced in this study will support more spatially resolved capacity expansion modeling and will help inform policy making at local and national levels.

capacity planning↗
DOE OSTI2018

Are We Adapting to Floods? Evidence from Global Flooding Fatalities

There has been a growing interest in understanding whether and how people adapt to extreme weather events in a changing climate. This article presents one of the first empirical analyses of adaptation to flooding on a global scale. Using a sample of 97 countries between 1985 and 2010, we investigate the extent and pattern of flood adaptation by estimating the effects of a country's climatological risk, recent flood experiences, and socioeconomic characteristics on its flood-related fatalities. Our results provide mixed evidence on adaptation: countries facing greater long-term climatological flooding risks do not necessarily adapt better and suffer fewer fatalities; however, after controlling for the cross-country heterogeneity, we find that more recent flooding shocks have a significant and negative effect on fatalities from subsequent floods. These findings may suggest the short-term learning dynamics of adaptation and potential inefficacy of earlier flood control measures, particularly those that promote increased exposure in floodplains. Our findings provide important implications for climate adaptation policy making and climate modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Next-generation wargames

Over the past century, and particularly since the outset of the Cold War, wargames (interactive simulations used to evaluate aspects of tactics, operations, and strategy) have become an integral means for militaries and policy-makers to evaluate how strategic decisions are made related to nuclear weapons strategy and international security. Furthermore, these methods have also been applied beyond the military realm, to examine phenomena as varied as elections, government policy, international trade, and supply-chain mechanics. Today, a renewed focus on wargaming combined with access to sophisticated and inexpensive drag-and-drop digital game development frameworks and new cloud computing architectures have democratized the ability to enable massive multiplayer gaming experiences. With the integration of simulation tools and experimental methods from a variety of social science disciplines, a science-based experimental gaming approach has the potential to transform the insights generated from gaming by creating human-derived, large-n datasets for replicable, quantitative analysis. In the following, we outline challenges associated with contemporary simulation and wargaming tools, investigate where scholars have searched for game data, and explore the utility of new experimental gaming and data analysis methods in both policy-making and academic settings.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2019

Visualizing urban microclimate and quantifying its impact on building energy use in San Francisco

© 2019 Association for Computing Machinery. Weather data at nearby airports are usually used in building energy simulation to estimate energy use in buildings or evaluate building design or retrofit options. However, due to urbanization and geography characteristics, local weather conditions can differ significantly from those at airports. This study presents the visualization of 10-year hourly weather data measured at 27 sites in San Francisco, aiming to provide insights into the urban microclimate and urban heat island effect in San Francisco and how they evolve during the recent decade. The 10-year weather data are used in building energy simulations to investigate its influence on energy use and electrical peak demand, which informs the city's policy making on building energy efficiency and resilience. The visualization feature is implemented in CityBES, an open web-based data and computing platform for urban building energy research.

Hong, T↗
DOE OSTI2024

A Visual Analytic Platform for Interactive Validation of Human Mobility Simulations

Human mobility insights guide domain experts in an array of decisions, including critical infrastructure design, disaster response, epidemic modeling, national security, and policy making. Due to the inherent noise and privacy concerns in real-world individual-level mobility data, it is often preferred to leverage simulators that generate synthetic mobility data instead. However, it is critical to inspect and validate the output of such simulators to ensure the synthetic data is aligned with the characteristics of the population and the area of interest known to domain experts. While there exist many quantitative approaches for validating synthetic data, we argue it is also important to also validate such data qualitatively to capture aspects that are known to domain experts but difficult to quantify. In this work, we demonstrate a visual analytic platform that empowers domain experts to interact with their simulation outputs along spatial and temporal dimensions. By augmenting automated techniques and human skills, our visual analytic platform is a step towards interactive capabilities for model steering and quality control of mobility simulators.

Monadjemi, Shayan↗
DOE OSTI2026

Toward a Climate OSSE Framework for Satellite Mission Design

The rich history of observing system simulation experiments (OSSEs) does not yet include a well-established framework for using climate models. The need for a climate OSSE is triggered by the need to quantify the value of a particular measurement for reducing the uncertainty in climate predictions, which differ from numerical weather predictions in that they depend on future atmospheric composition rather than the current state of the weather. However, both weather and climate modeling communities share a need for motivating major observing system investments. Here, we outline a new framework for climate OSSEs that leverages the use of machine learning to calibrate climate model physics against existing satellite data. We demonstrate its application using NASA’s GISS-E3 model to objectively quantify the value of potential future improvements in spaceborne measurements of Earth’s planetary boundary layer. A mature climate OSSE framework should be able to quantitatively compare the ability of proposed observing system architectures to answer a climate-related question, thus offering added value throughout the mission design process, which is subject to increasingly rapid advances in instrument and satellite technology. Technical considerations include selection of observational benchmarks and climate projection metrics, approaches to pinpoint the sources of model physics uncertainty that dominate uncertainty in projections, and the use of instrument simulators. Community and policy-making considerations include the potential to interface with an established culture of model intercomparison projects and a growing need to economically assess the value-driven efficiency of social spending on Earth observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Research on Anaerobic Digestion: Optimization and Scalability of Mixed High-strength Food Processing Wastes for Renewable Biogas Energy

This research project developed and improved anaerobic digestion technologies, created a comprehensive Inventory of Ohio Biomass and a database of microorganisms of anaerobic digesters, and advanced knowledge and understanding of the underpinning microbiology of the anaerobic digestion process. The results and finding of this research project may be useful for future development and implementation of anaerobic digesters, especially at livestock farms. Policy makers and investors may also find the information on the biomass availability in Ohio and valuation of energy projects useful in policy making and making of investment decisions. The public may benefit from the information on biogas as an energy source and the potential impact of anaerobic digester projects on their neighborhoods.

09 BIOMASS FUELS↗
DOE OSTI2013

Geochemical Impacts of Leaking CO 2 from Subsurface Storage Reservoirs to Unconfined and Confined Aquifers

Experimental research work has been conducted and is undergoing at Pacific Northwest National Laboratory (PNNL) to address a variety of scientific issues related with the potential leaks of the carbon dioxide (CO 2 ) gas from deep storage reservoirs. The main objectives of this work are as follows: • Develop a systematic understanding of how CO 2 leakage is likely to influence pertinent geochemical processes (e.g., dissolution/precipitation, sorption/desorption and redox reactions) in the aquifer sediments. • Identify prevailing environmental conditions that would dictate one geochemical outcome over another. • Gather useful information to support site selection, risk assessment, policy-making, and public education efforts associated with geological carbon sequestration. In this report, we present results from experiments conducted at PNNL to address research issues related to the main objectives of this effort. A series of batch and column experiments and solid phase characterization studies (quantitative x-ray diffraction and wet chemical extractions with a concentrated acid) were conducted with representative rocks and sediments from an unconfined, oxidizing carbonate aquifer, i.e., Edwards aquifer in Texas, and a confined aquifer, i.e., the High Plains aquifer in Kansas. These materials were exposed to a CO 2 gas stream simulating CO 2 gas leaking scenarios, and changes in aqueous phase pH and chemical composition were measured in liquid and effluent samples collected at pre-determined experimental times. Additional research to be conducted during the current fiscal year will further validate these results and will address other important remaining issues. Results from these experimental efforts will provide valuable insights for the development of site-specific, generation III reduced order models. In addition, results will initially serve as input parameters during model calibration runs and, ultimately, will be used to test model predictive capability and competency. The results from these investigations will provide useful information to support site selection, risk assessment, and public education efforts associated with geological, deep subsurface CO 2 storage and sequestration.

Qafoku, Nikolla P.↗
DOE OSTI2013

Active Measurement of Memory Resource Consumption

Hierarchical memory is a cornerstone of modern hardware design because it provides high memory performance and capacity at a low cost. However, the use of multiple levels of memory and complex cache management policies makes it very difficult to optimize the performance of applications running on hierarchical memories. As the number of compute cores per chip continues to rise faster than the total amount of available memory, applications will become increasingly starved for memory storage capacity and bandwidth, making the problem of performance optimization even more critical. We propose a new methodology for measuring and modeling the performance of hierarchical memories in terms on the application’s utilization of the key memory resources: capacity of a given memory level and bandwidth between two levels. This is done by actively interfering with the application’s use of these resources. The application’s sensitivity to reduced resource availability is measured by observing the effect of interference on application performance. The resulting resource-oriented model of performance both greatly simplifies application performance analysis and makes it possible to predict an application’s performance when running with various resource constraints. This is useful to predict performance for future memory-constrained architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

A Bottom-up Energy Efficiency Improvement Roadmap for China’s Iron and Steel Industry up to 2050

Iron and steel manufacturing is energy intensive in China and in the world. China is the world largest steel producer accounting for around half of the world steel production. In this study, we use a bottom-up energy consumption model to analyze four steel-production and energy-efficiency scenarios and evaluate the potential for energy savings from energy-efficient technologies in China’s iron and steel industry between 2010 and 2050. The results show that China’s steel production will rise and peak in the year 2020 at 860 million tons (Mt) per year for the base-case scenario and 680 Mt for the advanced energy-efficiency scenario. From 2020 on, production will gradually decrease to about 510 Mt and 400 Mt in 2050, for the base-case and advanced scenarios, respectively. Energy intensity will decrease from 21.2 gigajoules per ton (G/t) in 2010 to 12.2 GJ/t and 9.9 GJ/t in 2050 for the base-case and advanced scenarios, respectively. In the near term, decreases in iron and steel industry energy intensity will come from adoption of energy-efficient technologies. In the long term, a shift in the production structure of China’s iron and steel industry, reducing the share of blast furnace/basic oxygen furnace production and increasing the share of electric-arc furnace production while reducing the use of pig iron as a feedstock to electric-arc furnaces will continue to reduce the sector’s energy consumption. We discuss barriers to achieving these energy-efficiency gains and make policy recommendations to support improved energy efficiency and a shift in the nature of iron and steel production in China.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗