Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “INDICATORS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Covariance Propagation in Spectral Indices

The dosimetry community has a history of using spectral indices to support neutron spectrum characterization and cross section validation efforts. An important aspect to this type of analysis is the proper consideration of the contribution of the spectrum uncertainty to the total uncertainty in calculated spectral indices (SIs). This paper identifies deficiencies in the traditional treatment of the SI uncertainty, provides simple bounds to the spectral component in the SI uncertainty estimates, verifies that these estimates are reflected in actual applications, details a methodology that rigorously captures the spectral contribution to the uncertainty in the SI, and provides quantified examples that demonstrate the importance of the proper treatment the spectral contribution to the uncertainty in the SI.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Community Resilience Indicator Analysis: Commonly Used Indicators from Peer-Reviewed Research (Updated for Research Published 2003-2021)

In 2017, FEMA’s National Integration Center (NIC) Technical Assistance (TA) Branch identified a need to establish a data-driven basis for prioritizing locations for TA investment and guiding local emergency management planning. To achieve this goal, FEMA tasked Argonne National Laboratory (Argonne) with identifying commonly used indicators of community resilience across the landscape of published peer-reviewed research. FEMA and Argonne completed the first Community Resilience Indicator Analysis (CRIA) in 2018 and repeated the process in 2022. The CRIA process begins with a literature review and cataloguing of published peer-reviewed assessment methodologies on social vulnerability and community resilience. The literature review findings are then filtered by inclusion criteria established by the CRIA research team to ensure the methodologies are: (1) Quantitative, (2) Data and methodology are publicly available, (3) Calculated at the county level or lower, (4) Examine generalized hazard risk (rather than a singular hazard), and (5) Focused on pre-disaster community conditions. After this, the research team identifies the commonly used indicators across these methodologies and selects the best data source for each indicator. Finally, the research team bins the data for visual display, conducts a correlation analysis and creates a composite index, the FEMA Community Resilience Index (FEMA CRI). In 2018, the CRIA identified eight resilience and vulnerability assessment methodologies and 20 commonly used indicators (indicators used in three or more of the eight methodologies). The FEMA CRI in 2018 was created from these 20 indicators and was produced for at the county level. The 2022 CRIA updated the literature review to expand the list of methodologies examined and followed the same process, resulting in an analysis of 14 methodologies published between 2003 and 2021 and 22 indicators identified as commonly used (indicators used in five or more of the 14 methodologies). In 2022, the research team produced the FEMA CRI at the county and the census tract levels. To make the CRIA data more accessible and more actionable, each individual indicator and the FEMA CRI is binned and included in FEMA’s Resilience Analysis and Planning Tool (RAPT). RAPT enables emergency managers and community partners to quickly visualize relative differences in potential resilience by county, tribe and census tract. By reviewing the data for each of these 22 indicators individually, emergency managers can gain insights for targeted outreach strategies, planning, mitigation investments and response and recovery operations. Communities, regional governments and others can use this data to better understand potential challenges to resilience. As the social science field of examining and validating indicators of resilience evolves, FEMA will update RAPT to provide emergency managers and community partners with additional data and tools to inform planning, mitigation, response and recovery. It is important to understand that the role of the emergency manager is not to change or to “improve” the data, but to plan appropriately for the community characteristics reflected in the data. These datasets are community characteristics that researchers have identified as important considerations for resilience. For example, people with disabilities may have greater challenges to be resilient to disasters. If a community has a high population of people with disabilities, the emergency manager(s) may need to create tailored preparedness outreach programs and strategies to ensure those residents have support if evacuation is necessary. Rather than label these indicators as an absolute measure of resilience, FEMA considers “potential challenges to resilience” a better frame to understand these indicators. Everyone is vulnerable to disasters. While scholars theorize that certain characteristics may make an individual or a household more socially vulnerable, the data does not reflect measures that individuals and/or communities have taken to address potential challenges, such as emergency management planning and outreach or household preparedness measures. To aid emergency managers in understanding how to use these indicators, calling them potential challenges to resilience supports a more positive and strategic application of the data in all phases of emergency management.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Latitudinal and energy dependence of energetic neutral atom spectral indices measured by the Interstellar Boundary Explorer

We investigate the latitudinal and energy dependence of the globally distributed 0.5–6 keV energetic neutral atom (ENA) spectra measured by the Interstellar Boundary Explorer (IBEX) during the first 3 yrs of the mission. Our results are: (1) the ENA spectral indices at the two lowest energies (0.89 and 1.47 keV) exhibit no clear trend with ecliptic latitude θ, while those at ∼2.29 and ∼3.41 keV exhibit a clear latitudinal pattern; flatter spectra occur above 60° latitude and steeper spectra occur ±30° of the equator. (2) The latitudinal dependence of the spectral indices at different energies can be represented by the cosine function γ=a{sub 0}+a{sub 1}cos(a{sub 2}θ) with unique offsets, amplitudes, and phase angles; the higher energy ENA indices transition to successively larger amplitudes within ±45° of the equator. Our results confirm the previously reported latitudinal organization of the ENA spectra and their remarkable similarity to that of the solar wind (SW) speed observed by Ulysses in the inner heliosphere. While earlier studies showed that the ∼0.5–6 keV globally distributed ENA spectral indices could be represented as single power laws over much of the sky, our new results indicate that this is an over-simplification because the spectral indices have an energy and latitude dependence. This dependence is an important factor that must be taken into consideration by models and simulations that seek to map the IBEX ENA observations back to the latitudinal profile of the SW speed structure observed in the inner heliosphere.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Multiple uses of indicators and indices in cumulative effects assessment and management

Both environmental indicators and multi-metric indices are useful for describing baseline conditions and qualitatively predicting the cumulative consequences of multiple actions. Several examples and case studies associated with indicators and/or indices are presented herein. They can be easily modified for usage in CEAM. Habitat suitability models reflect special indices related to habitat needs and quality for specific species or broad habitat types. Such models have been used to address direct and indirect effects, and with some modification, they can be also used to address cumulative effects of multiple actions. This review has indicated that there are numerous examples of such tools which have been or could be used in both EIA and CEAM. Some key lessons are: (1) in conducting CEAM studies, it is useful to think from the mindset that 'I am the VEC or indicator, and what is my historical and current condition and how have I, or will I, be affected by multiple past, present, and future actions?'; (2) due to the likely absence of detailed information on future actions, the described tools can still be used to 'predict' future conditions by focusing on qualitative up-or-down changes in individual indicators or indices with their aggregated displays; and (3) numerous regional and site-specific tools are currently available, with one example being indices of biological integrity for specific watersheds and water bodies. Such tools, even though they may not have been developed for CEAM usage, can certainly benefit CEAM studies and practice. Finally, usage of selected and appropriate tools as described herein can aid in conducting science-based, systematic, and documentable CEAM studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Data-Driven Robust M-LS-SVR-Based NARX Modeling for Estimation and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking

Optimal operation of an industrial blast furnace (BF) ironmaking process largely depends on a reliable measurement of molten iron quality (MIQ), which is not feasible using the conventional sensors. This paper proposes a novel data-driven robust modeling method for online estimation and control of MIQ indices. First, to completely capture the nonlinear dynamics of the BF process, the nonlinear autoregressive exogenous (NARX) model is constructed for the MIQ indices. Then, considering that the standard least-squares support vector regression (LS-SVR) cannot directly cope with the multi-output problem, the multi- task transfer learning is proposed to design a novel multi-output LS-SVR (M-LS-SVR) for learning of the NARX model. Furthermore, a novel M-estimator is proposed to reduce the interference of outliers and improve the robustness of the M-LS- SVR model. Since the weights of different outlier data are properly given by the weight function, their corresponding contributions on modeling can be properly distinguished, thus a robust modeling result can be achieved. Finally, a novel multi- objective evaluation index on modeling performance is developed by comprehensively considering the root mean square error of modeling and the correlation coefficient on trend fitting, based on which the NSGA-II algorithm is used to globally optimize the model parameters. Both experiments using industrial data and industrial applications illustrate that the proposed method can eliminate the adverse effect caused by the fluctuation of data in BF process efficiently, which indicates its stronger robustness and higher accuracy. Moreover, control testing shows that the developed model can be well applied to realize data-driven control of the BF process.

blast cavities, Control↗
DOE OSTI2021

Is satellite Sun-Induced Chlorophyll Fluorescence more indicative than vegetation indices under drought condition?

Droughts represent one of the most severe abiotic stress factors that could result in great crop yield loss. Numerous vegetation indices have been proposed for monitoring the vegetation condition under stress and assessing drought impacts on yield loss. However, the understanding and comparison between traditional vegetation indices (VIs) and the newly emerging satellite Sun-Induced Chlorophyll Fluorescence (SIF) for monitoring vegetation condition is still limited especially under drought stress and at multiple spatial scales. In this study, the potential of satellite observation SIF for monitoring corn response to drought was investigated based on the 2012 drought in the US Corn Belt. The standardized precipitation evapotranspiration index (SPEI) was used here to quantify drought. We found that all SPEI were above –1, except for July (–1.27), August (–1.39) and September (–1.14) in 2012, indicating the severity of this drought. We examined the relationship between satellite measurements of SIF, SIF yield , VIs (e.g., NDVI and EVI) and SPEI. Results indicated that SIF yield was sensitive to drought and SIF captured the stress more accurately both at the regional and state scales for the US Corn Belt. Quantitatively, SIF yield had a high correlation with SPEI (r = 0.987, p < 0.05) over the entire Corn Belt, and it indicated losses in response to drought approximately one month earlier than SIF/NDVI/EVI. Furthermore, our results demonstrated that SIF could be trusted as an effective indicator to study the relationship between GPP (R 2 ≥ 0.8664, p < 0.01) under drought conditions across the Corn Belt. Finally, this study highlighted the advantage of using satellite SIF observations to monitor the drought stress on crop growth especially GPP at regional scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Indicators of Global Climate Change 2023: annual update of key indicators of the state of the climate system and human influence

Intergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC). Evidence-based decision-making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on the global climate system. However, successive IPCC reports are published at intervals of 5–10 years, creating potential for an information gap between report cycles. We follow methods as close as possible to those used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report. We compile monitoring datasets to produce estimates for key climate indicators related to forcing of the climate system: emissions of greenhouse gases and short-lived climate forcers, greenhouse gas concentrations, radiative forcing, the Earth's energy imbalance, surface temperature changes, warming attributed to human activities, the remaining carbon budget, and estimates of global temperature extremes. The purpose of this effort, grounded in an open-data, open-science approach, is to make annually updated reliable global climate indicators available in the public domain. As they are traceable to IPCC report methods, they can be trusted by all parties involved in UNFCCC negotiations and help convey wider understanding of the latest knowledge of the climate system and its direction of travel. The indicators show that, for the 2014–2023 decade average, observed warming was 1.19 [1.06 to 1.30] °C, of which 1.19 [1.0 to 1.4] °C was human-induced. For the single-year average, human-induced warming reached 1.31 [1.1 to 1.7] °C in 2023 relative to 1850–1900. The best estimate is below the 2023-observed warming record of 1.43 [1.32 to 1.53] °C, indicating a substantial contribution of internal variability in the 2023 record. Human-induced warming has been increasing at a rate that is unprecedented in the instrumental record, reaching 0.26 [0.2–0.4] °C per decade over 2014–2023. This high rate of warming is caused by a combination of net greenhouse gas emissions being at a persistent high of 53±5.4 Gt CO 2 e yr -1 over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that the rate of increase in CO 2 emissions over the last decade has slowed compared to the 2000s, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track a change of direction for some of the indicators presented here.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Application of Biochemical and Physiological Indicators for Assessing Recovery of Fish Populations in a Disturbed Stream

Recovery dynamics in a previously disturbed streamwere investigated to determine the influence of a series of remedial actions on stream recovery and to evaluate the potential application of bioindicators as an environmental management tool. A suite of bioindicators, representing five different functional response groups, were measured annually for a sentinel fish species over a 15 year period during which a variety of remedial and pollution abatement actions were implemented. Trends in biochemical, physiological, condition, growth, bioenergetic, and nutritional responses demonstrated that the health status of a sentinel fish species in the disturbed stream approached that of fish in the reference stream by the end of the study. Two major remedial actions, dechlorination and water flow management, had large effects on stream recovery resulting in an improvement in the bioenergetic, disease, nutritional, and organ condition status of the sentinel fish species. A subset of bioindicators responded rather dramatically to temporal trends affecting all sites, but some indicators showed little response to disturbance or to restoration activities. In assessing recovery of aquatic systems, application of appropriate integrative structural indices along with a variety of sensitive functional bioindicators should be used to understand the mechanistic basis of stress and recovery and to reduce the risk of false positives. Understanding the mechanistic processes involved between stressors, stress responses of biota, and the recovery dynamics of aquatic systems reduces the uncertainty involved in environmental management and regulatory decisions resulting in an increased ability to predict the consequences of restoration and remedial actions for aquatic systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Review of sustainability indices and indicators: Towards a new City Sustainability Index (CSI)

The purpose of this paper is to discuss conceptual requirements for a City Sustainability Index (CSI) and to review existing major sustainability indices/indicators in terms of the requirements. The following indices are reviewed: Ecological Footprint (EF), Environmental Sustainability Index (ESI), Dashboard of Sustainability (DS), Welfare Index, Genuine Progress Indicator (GPI), Index of Sustainable Economic Welfare, City Development Index, emergy/exergy, Human Development Index (HDI), Environmental Vulnerability Index (EVI), Environmental Policy Index (EPI), Living Planet Index (LPI), Environmentally-adjusted Domestic Product (EDP), Genuine Saving (GS), and some applications of composite indices or/and multivariate indicators to local or regional context as case studies. The key conceptual requirements for an adequate CSI are: (i) to consider environmental, economic and social aspects (the triple bottom line of sustainability) from the viewpoint of strong sustainability; (ii) to capture external impacts (leakage effects) of city on other areas beyond the city boundaries particularly in terms of environmental aspects; (iii) to create indices/indicators originally for the purpose of assessing city sustainability; and (iv) to be able to assess world cities in both developed and developing countries using common axes of evaluation. Based on the review, we conclude that it is necessary to create a new CSI that enables us to assess and compare cities' sustainability performance in order to understand the global impact of cities on the environment and human life as compared with their economic contribution. In the future, the CSI will be able to provide local authorities with guidance toward sustainable paths. - Highlights: Black-Right-Pointing-Pointer We derive the four key requirements for a new City Sustainability Index (CSI) system. Black-Right-Pointing-Pointer First, the triple bottom line must be considered in terms of strong sustainability. Black-Right-Pointing-Pointer Second, environmental leakage effects beyond city boundaries should be captured. Black-Right-Pointing-Pointer Third, 'city sustainability' should be originally considered when CSI is created. Black-Right-Pointing-Pointer Fourth, cities in developed and developing countries can be evaluated without bias.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Association between human and animal thermal comfort indices and physiological heat stress indicators in dairy calves

Warm summer episodes have a significant effect on the overall health and well-being of young cattle; however, it is not known which temperature measure should be used for estimating heat stress in dairy calves. In this study, generalized linear mixed-effects models were used to estimate the relationships between thermal comfort indices and animal-based heat stress indicators in sixteen Holstein bull calves that were housed in individual calf hutches. Data were collected under continental weather characteristics over a 5-day period: day 1 (lower-temperature day), days 2 and 3 (heat stress days), and a 2-day post-stress period. Relative humidity, ambient temperature, the heat index, the humidex and five different temperature–humidity indices (THI) were used as thermal indices. Physiological variables monitored included respiratory rate, rectal temperature, ear skin temperature and heart rate. The heat index and the humidex measuring human thermal comfort were more closely associated with physiological measures than were the ambient temperature or the THIs (in case of heat index: R{sup 2} = 0.87 for respiratory rate, R{sup 2} = 0.63 for rectal temperature, R{sup 2} = 0.70 for ear skin temperature, and R{sup 2} = 0.78 for heart rate, respectively; in case of humidex: R{sup 2} = 0.85 for respiratory rate, R{sup 2} = 0.60 for rectal temperature, R{sup 2} = 0.68 for ear skin temperature, and R{sup 2} = 0.75 for heart rate, respectively). Based on our results, parameters of human outdoor comfort seem better to estimate heat stress in dairy calves in a continental region than those of THIs or ambient temperature.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Refractive indices in the whole transmission range of partially deuterated KDP crystals

Refractive indices of partially deuterated potassium dihydrogen phosphate (DKDP) crystals with 55%, 70% and 80% deuterium contents were measured by auto-collimation method at 293 K between 0.254 to 1.529 μm. Dependence of refractive indices of DKDP on deuterium content show different trend in the infrared region as in uv-visible region. Dependence of n{sup 2} (the square of refractive index) on the mole fraction of deuterium shows a difference between pure KDP and partially deuterated KDP. The Sellmeier equations were obtained by the least square method. The non-critical phase matching angles calculated from the fitted formula were in good agreement with laser experiment results, by which the reliability of these Sellmeier equations was confirmed.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Energy Saving Melting and Revert Reduction Technology (Energy-SMARRT): Surface/Near Surface Indication - Characterization of Surface Anomalies from Magnetic Particle and Liquid Penetrant Indications

The systematic study and characterization of surface indications has never been conducted. Producers and users of castings do not have any data on which they can reliably communicate the nature of these indications or their effect on the performance of parts. Clearly, the ultimate intent of any work in this area is to eliminate indications that do in fact degrade properties. However, it may be impractical physically and/or financially to eliminate all surface imperfections. This project focused on the ones that actually degrade properties. The initial work was to identify those that degrade properties. Accurate numerical simulations of casting service performance allow designers to use the geometric flexibility of castings and the superior properties of steel to produce lighter weight and more energy efficient components for transportation systems (cars and trucks), construction, and mining. Accurate simulations increase the net melting energy efficiency by improving casting yield and reducing rework and scrap. Conservatively assuming a 10% improvement in yield, approximately 1.33 x 10 12 BTU/year can be saved with this technology. In addition, CO 2 emissions will be reduced by approximately 117,050 tons per year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Comparing Multipollutant Emissions-Based Mobile Source Indicators to Other Single Pollutant and Multipollutant Indicators in Different Urban Areas

A variety of single pollutant and multipollutant metrics can be used to represent exposure to traffic pollutant mixtures and evaluate their health effects. Integrated mobile source indicators (IMSIs) that combine air quality concentration and emissions data have recently been developed and evaluated using data from Atlanta, Georgia. IMSIs were found to track trends in traffic-related pollutants and have similar or stronger associations with health outcomes. In the current work, we apply IMSIs for gasoline, diesel and total (gasoline + diesel) vehicles to two other cities (Denver, Colorado and Houston, Texas) with different emissions profiles as well as to a different dataset from Atlanta. We compare spatial and temporal variability of IMSIs to single-pollutant indicators (carbon monoxide (CO), nitrogen oxides (NOx) and elemental carbon (EC)) and multipollutant source apportionment factors produced by Positive Matrix Factorization (PMF). Across cities, PMF-derived and IMSI gasoline metrics were most strongly correlated with CO (r = 0.31–0.98), while multipollutant diesel metrics were most strongly correlated with EC (r = 0.80–0.98). NOx correlations with PMF factors varied across cities (r = 0.29–0.67), while correlations with IMSIs were relatively consistent (r = 0.61–0.94). In general, singlepollutant metrics were more correlated with IMSIs (r = 0.58–0.98) than with PMF-derived factors (r = 0.07–0.99). A spatial analysis indicated that IMSIs were more strongly correlated (r > 0.7) between two sites in each city than single pollutant and PMF factors. These findings provide confidence that IMSIs provide a transferable, simple approach to estimate mobile source air pollution in cities with differing topography and source profiles using readily available data.

mobile sources↗
DOE OSTI2019

Delineating Facies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics with Level-Set Transformation

The facies-based approach has been widely adopted to delineate an aquifer into distinct geological units with unique distributions of hydraulic, physical, and/or chemical properties. The recent development in ensemble-based data assimilation methods allows both the direct and indirect data to be used to improve facies delineation. A major difficulty in those applications is to honor the spatial continuity and avoid overfitting after data assimilation. We introduce a new facies delineation framework to integrate ensemble data assimilation with traditional transition probability-based geostatistics. A level-set concept is used to parametrize discrete facies indicators and for updating facies shape. During the iterative data assimilation process, we impose spatial continuity by conditioning facies field generation on points selected adaptively based on their sensitivity to observation data. This reconditioning step is a key step to maintain spatial continuity and overcome over-fitting problems in inversion. We selected two examples to evaluate the performance of the new framework in estimating facies-based permeability field. The first example is a two-dimensional synthetic system with transient head data induced by pumping tests used for delineating two facies. The second example is a three-dimensional case with three facies, conceptualized from a field tracer experiment within the Columbia River corridor in Washington State, USA. Both examples demonstrate that the new method can adequately capture the spatial pattern of hydrofacies with reconditioning, which leads to the improved prediction of system behaviors.

Song, Xuehang↗
DOE OSTI2016

Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Indication on the Process Dependence of the Sivers Effect

We analyze the spin asymmetry for single inclusive jet production in proton-proton collisions collected by the AnDY experiment at the Relativistic Heavy Ion Collider and the Sivers asymmetry data from semi-inclusive deep inelastic scattering experiments. In particular, we consider the role color gauge invariance plays in determining the process dependence of the Sivers effect. We find that after carefully taking into account the initial-state and final-state interactions between the active parton and the remnant of the polarized hadron, the calculated jet spin asymmetry based on the Sivers functions extracted from HERMES and COMPASS experiments is consistent with the AnDY experimental data. This provides a first indication for the process dependence of the Sivers effect in these processes. Furthermore, we also make predictions for both direct photon and Drell-Yan spin asymmetry, to further test the process dependence of the Sivers effect in future experiments.

Gamberg, Leonard↗