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At least 235 records · Page 13

Prairie State Generating Company Static and Dynamic Modeling

A reservoir modeling study was conducted to assess the feasibility of storing 162.5 million tonnes (8.125 million tonnes annually) of industrially sourced carbon dioxide (CO 2 ) in the St. Peter – Everton and Knox storage complexes at the Prairie State Generating Company’s (PSGC) site near Marissa, Washington County, Illinois (PSGC site). Two separate models were constructed for the St. Peter – Everton and the Knox storage complexes. The St. Peter and Everton sandstones are the target storage units for the St. Peter – Everton storage complex. The Knox Group formations are the target storage units for the Knox storage complex. The Maquoketa Shale is the primary confining unit for both storage complexes. The static reservoir models used as input to the dynamic reservoir models of the storage complexes were developed from interpretations of logs (e.g., gamma ray, resistivity, porosity, photoelectric, and sonic), structure surfaces using data from 36 wells, thickness maps, well test data, seismic data, and permeability data in PetrelTM.

01 COAL, LIGNITE, AND PEAT↗

Energy Cost Analysis and Operational Range Prediction Based on Medium- and Heavy-Duty Electric Vehicle Real-World Deployments across the United States

While the market for medium- and heavy-duty battery-electric vehicles (MHD EVs) is still nascent, a growing number of these vehicles are being deployed across the U.S. This study used over 2.3 million miles of operational data from multiple types of MHD EVs across various regions and operating conditions to address knowledge gaps in total cost of ownership and operational range. First, real-world energy cost savings were determined: MHD fleets should experience energy cost savings each year from 2021 to 2035, regardless of vehicle platform, with the greatest savings seen in transit buses (up to USD 4459 annually) and HD trucks (up to USD 3284 annually). Second, to help fleets across various geographies throughout the U.S. assess the suitability of EVs for their year-round operating needs, operational range was modeled using the XGBoost algorithm (R2: 70%) given 22 input features relevant to vehicle efficiency. Finally, this paper recommends (1) that MHD fleets apply energy-saving practices to minimize the impacts of cold temperatures and high congestion levels on vehicle efficiency and range, and (2) that local hauling fleets select trucks with a nominal range nearly double the expected maximum daily range to account for range losses under local, urban driving conditions.

Qiu, Yin (ORCID:0009000900948794)↗

Economic considerations in coverting from oil/gas firing to coal

Economic considerations involved in fuel conversion such as from oil and/or gas firing to coal are discussed including investments costs for new facilities and equipment (including air pollution control equipment), operation and maintenance costs, and purchased fuel costs. An analytical approach to assessing the cost effectiveness of fuel conversion in terms of the annual net cost of conversion, the equivalent annual number of barrels of oil saved, and the integral rate of return of the conversion investment is presented. Illustrative numerical examples are presented for typical utility boilers and industrial boiler facilities. A further consideration addressed deals with the impacts of these costs on the overall financial structure of the firm and the ability of the firm to raise the necessary investment captial.

Rau, J. G.↗

Characterizing Urban Heat Islands of Global Settlements Using MODIS and Nighttime Lights Products

Impervious surface area (ISA) from the National Geophysical Data Center (NGDC) and land surface temperature (LST) from MODIS averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) signature on LST amplitude and its relationship to development intensity, size, and ecological setting for more than 3000 urban settlements over the globe. Development intensity zones based on fractional ISA are defined for each urban area emanating outward from the urban core to the nearby non-urban rural areas and used to stratify sampling for LST. Sampling is further constrained by biome type and elevation data to insure objective inter-comparisons between zones and between cities in different biomes. We find that the ecological context and settlement size significantly influence the amplitude of summer daytime UHI. Globally, an average of 3.8 C UHI is found in cities built in biomes dominated by forests; 1.9 C UHI in cities embedded in grass/shrub biomes, and only a weak UHI or sometimes an Urban Heat Sink (UHS) in cities in and and semi-arid biomes. Overall, the amplitude of the UHI is negatively correlated (R = -0.66) to the difference in vegetation density between urban and rural zones represented by MODIS Normalized Difference Vegetation Index (NDVI). Globally averaged, the daytime UHI amplitude for all settlement is 2.6 C in summer and 1.4 C in winter. Globally, the average summer daytime UHI is 4.7 C for settlements larger than 500 square kilometers, compared to 2.5 C for settlements smaller than 50 square kilometers and larger than 10 square kilometers. The stratification of cities by size indicates that the aggregated amount of ISA is the primary driver of UHI amplitude with variations between ecological contexts and latitudinal zones. More than 60% of the total LST variances is explained by ISA for urban settlements within forests at mid-to-high latitudes. This percentage will increase to more than 80% when only USA settlements are examined.

Zhang, Ping↗

Remote Sensing of the Urban Heat Island Effect Across Biomes in the Continental USA

Impervious surface area (ISA) from the Landsat TM-based NLCD 2001 dataset and land surface temperature (LST) from MODIS averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) skin temperature amplitude and its relationship to development intensity, size, and ecological setting for 38 of the most populous cities in the continental United States. Development intensity zones based on %ISA are defined for each urban area emanating outward from the urban core to the nonurban rural areas nearby and used to stratify sampling for land surface temperatures and NDVI. Sampling is further constrained by biome and elevation to insure objective intercomparisons between zones and between cities in different biomes permitting the definition of hierarchically ordered zones that are consistent across urban areas in different ecological setting and across scales. We find that ecological context significantly influences the amplitude of summer daytime UHI (urban-rural temperature difference) the largest (8 C average) observed for cities built in biomes dominated by temperate broadleaf and mixed forest. For all cities combined, ISA is the primary driver for increase in temperature explaining 70% of the total variance in LST. On a yearly average, urban areas are substantially warmer than the non-urban fringe by 2.9 C, except for urban areas in biomes with arid and semiarid climates. The average amplitude of the UHI is remarkably asymmetric with a 4.3 C temperature difference in summer and only 1.3 C in winter. In desert environments, the LST's response to ISA presents an uncharacteristic "U-shaped" horizontal gradient decreasing from the urban core to the outskirts of the city and then increasing again in the suburban to the rural zones. UHI's calculated for these cities point to a possible heat sink effect. These observational results show that the urban heat island amplitude both increases with city size and is seasonally asymmetric for a large number of cities across most biomes. The implications are that for urban areas developed within forested ecosystems the summertime UHI can be quite high relative to the wintertime UHI suggesting that the residential energy consumption required for summer cooling is likely to increase with urban growth within those biomes.

Imhoff, Marc L.↗

Exploring the Influence of Impervious Surface Density and Shape on Urban Heat Islands in the Northeast USA Using MODIS and Landsat

Impervious surface area (ISA) from the National Land Cover Database (NLCD) 2001 and land surface temperature (LST) from MODIS averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) signature and its relationship to settlement size and shape, development intensity distribution, and land cover composition for 42 urban settlements embedded in forest biomes in the Northeastern United States. Development intensity zones, based on percent ISA, are defined for each urban area emanating outward from the urban core to nearby rural areas and are used to stratify land surface temperature. The stratification is further constrained by biome type and elevation to insure objective intercomparisons between urban zones within an urban settlement and between settlements. Stratification based on ISA allows the definition of hierarchically ordered urban zones that are consistent across urban settlements and scales. In addition to the surrounding ecological context, we find that the settlement size and shape as well as the development intensity distribution significantly influence the amplitude of summer daytime UHI. Within the Northeastern US temperate broadleaf mixed forest, UHI magnitude is positively related to the logarithm of the urban area size. Our study indicates that for similar urban area sizes, the development intensity distribution is one of the major drivers of UHI. In addition to urban area size and development intensity distribution, this analysis shows that both the shape of the urban area and the land cover composition in the surrounding rural area play an important role in modulating the UHI magnitude in different urban settlements. Our results indicate that remotely sensed urban area size and shape as well as the development intensity distribution influence UHI amplitude across regional scales.

Zhang, Ping↗

Characterizing Urban Heat Islands of Global Settlements Using MODIS and Nighttime Lights Products

Impervious surface area (ISA) from the National Geophysical Data Center (NGDC) and land surface temperature (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS) averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) signature on LST amplitude and its relationship with development intensity, size, and ecological setting for more than 3000 urban settlements globally. Development intensity zones based on fractional ISA are defined for each urban area emanating outward from the urban core to the nearby nonurban rural areas and used to stratify sampling for LST. Sampling is further constrained by biome type and elevation data to ensure objective intercomparisons between zones and between cities in different biomes. We find that the ecological context and settlement size significantly influence the amplitude of summer daytime UHI. Globally, an average of 3.8 C UHI is found in cities built in biomes dominated by forests; 1.9 C UHI in cities embedded in grass shrubs biomes; and only a weak UHI or sometimes an urban heat sink (UHS) in cities in arid and semi-arid biomes. Overall, the amplitude of the UHI is negatively correlated (R = -0.66) with the difference in vegetation density between urban and rural zones represented by the MODIS normalized difference vegetation index (NDVI). Globally averaged, the daytime UHI amplitude for all settlements is 2.6 C in summer and 1.4 C in winter. Globally, the average summer daytime UHI is 4.7 C for settlements larger than 500 square kilometers compared with 2.5 C for settlements smaller than 50 square kilometers and larger than 10 square kilometers. The stratification of cities by size indicates that the aggregated amount of ISA is the primary driver of UHI amplitude, with variations between ecological contexts and latitudinal zones. More than 60% of the total LST variance is explained by ISA for urban settlements within forests at mid to high latitudes. This percentage will increase to more than 80% when only settlements in the US are examined.

Zhang, Ping↗

How Does Home Energy Score Affect Home Value and Mortgage Performance?

Energy-efficient homes save their occupants money through lower energy bills. These savings might be capitalized into higher home sale prices. They also improve the household’s net cash flow, which might make households better able to pay mortgage debt. The U.S. Department of Energy (DOE)’s Home Energy Score (HES) assigns a 1-10 score to homes and estimates annual energy bills based on modeled energy consumption. In this paper we investigated the relationship between HES metrics and two housing market outcomes: home sale price and mortgage performance. We found that the relationship was only statistically significant in places with a mandatory HES assessment at the time of sale. Using a sample of 26,291 home sales that occurred after HES assessments, we found that a one-point increase in HES in these locations was associated with a 0.5% increase in sale price, and an increase in $100 of estimated annual energy bills was associated with a 0.4% decrease. This magnitude of effect is consistent with estimated magnitudes of home sale premiums for other green or energy-efficient home certifications in the literature. We also found that a one-point increase in HES was associated with a 5.5% reduction in the odds of a loan going 30 days delinquent if the loan originated after the assessment occurred. Similarly, we found that a $100 decrease in estimated annual energy bills was associated with a 2.3% decrease in the odds of a loan going delinquent if it originated after the assessment occurred. Our results suggest that HES provides a valuable signal for housing market transactions in specific situations.

Pigman, Margaret↗

Multivariate Frequency Analysis of Annual Maxima Suspended Sediment Concentrations and Floods in the Jinsha River, China

Streamflow plays a critical role in sediment transport. Traditional frequency analysis of annual maximal (AM) suspended sediment concentrations (SSCs) is usually based on univariate distribution of SSCs and may provide a limited assessment of SSC state, leading to an underestimate or overestimate of the corresponding probability. To address this issue, we propose a multivariate frequency analysis framework is proposed for extreme sediment events using copula functions that account for the joint behavior of SSC and flood flow (i.e., peak discharge and volume). The uncertainties associated with copula modeling are also discussed. The Jinsha River in China is used as a case study. The results show that the copula-based multivariate method provides a more comprehensive assessment of extreme SSCs and their recurrence intervals than univariate frequency analysis. The uncertainty of copula modeling decreases with longer observation time and increases with larger return periods. The uncertainty ranges of the most likely design quantiles vary with different copulas, and the uncertainty range for the best-fit copula is not the smallest. This study is useful for the risk assessment of extreme SSC events under flood conditions.

42 ENGINEERING↗

Meteoroid Environment Modeling: the Meteoroid Engineering Model and Shower Forecasting

The meteoroid environment is often divided conceptually into meteor showers plus a sporadic background component. The sporadic complex poses the bulk of the risk to spacecraft, but showers can produce significant short-term enhancements of the meteoroid flux. The Meteoroid Environment Office (MEO) has produced two environment models to handle these cases: the Meteoroid Engineering Model (MEM) and an annual meteor shower forecast. Both MEM and the forecast are used by multiple manned spaceflight projects in their meteoroid risk evaluation, and both tools are being revised to incorporate recent meteor velocity, density, and timing measurements. MEM describes the sporadic meteoroid complex and calculates the flux, speed, and directionality of the meteoroid environment relative to a user-supplied spacecraft trajectory, taking the spacecraft's motion into account. MEM is valid in the inner solar system and offers near-Earth and cis-lunar environments. While the current version of MEM offers a nominal meteoroid environment corresponding to a single meteoroid bulk density, the next version of MEMR3 will offer both flux uncertainties and a density distribution in addition to a revised near-Earth environment. We have updated the near-Earth meteor speed distribution and have made the first determination of uncertainty in this distribution. We have also derived a meteor density distribution from the work of Kikwaya et al. (2011). The annual meteor shower forecast takes the form of a report and data tables that can be used in conjunction with an existing MEM assessment. Fluxes are typically quoted to a constant limiting kinetic energy in order to comport with commonly used ballistic limit equations. For the 2017 annual forecast, the MEO substantially revised the list of showers and their characteristics using 14 years of meteor flux measurements from the Canadian Meteor Orbit Radar (CMOR). Defunct or insignificant showers were removed and the temporal profiles of many showers were improved. In 2016 the MEO also adapted the forecast to the cislunar environment for the first time. We plan to make additional improvements to the model in the next two years using optical meteor flux measurements and mass indices.

Moorhead, Althea V.↗

Meteoroid Environment Modeling: the Meteoroid Engineering Model and Shower Forecasting

The meteoroid environment is often divided conceptually into meteor showers plus a sporadic background component. The sporadic complex poses the bulk of the risk to spacecraft, but showers can produce significant short-term enhancements of the meteoroid flux. The Meteoroid Environment Office (MEO) has produced two environment models to handle these cases: the Meteoroid Engineering Model (MEM) and an annual meteor shower forecast. Both MEM and the forecast are used by multiple manned spaceflight projects in their meteoroid risk evaluation, and both tools are being revised to incorporate recent meteor velocity, density, and timing measurements. MEM describes the sporadic meteoroid complex and calculates the flux, speed, and directionality of the meteoroid environment relative to a user-supplied spacecraft trajectory, taking the spacecraft's motion into account. MEM is valid in the inner solar system and offers near-Earth and cis-lunar environments. While the current version of MEM offers a nominal meteoroid environment corresponding to a single meteoroid bulk density, the next version of MEMR3 will offer both flux uncertainties and a density distribution in addition to a revised near-Earth environment. We have updated the near-Earth meteor speed distribution and have made the first determination of uncertainty in this distribution. We have also derived a meteor density distribution from the work of Kikwaya et al. (2011). The annual meteor shower forecast takes the form of a report and data tables that can be used in conjunction with an existing MEM assessment. Fluxes are typically quoted to a constant limiting kinetic energy in order to comport with commonly used ballistic limit equations. For the 2017 annual forecast, the MEO substantially revised the list of showers and their characteristics using 14 years of meteor flux measurements from the Canadian Meteor Orbit Radar (CMOR). Defunct or insignificant showers were removed and the temporal profiles of many showers were improved. In 2016 the MEO also adapted the forecast to the cislunar environment for the first time. We plan to make additional improvements to the model in the next two years using optical meteor flux measurements and mass indices.

Moorhead, Althea V.↗

Opportunities for Using the Industrial Assessment Center Database for Industrial Water Use Analysis

The manufacturing sector accounted for approximately 5–6% of total U.S. water use in 2015. Of that amount, 75–80% is self supplied withdrawal from surface-water and groundwater sources and the remainder is from public water supplies. Although manufacturing facilities commonly locate in water-scarce areas, water scarcity still poses a great risk to the manufacturing sector. Reliable water is necessary for any facility that relies on it for process and comfort cooling, cleaning, employee use, and steam generation. One of these barriers to water efficiency is the lack of reliable data on overall U.S. industrial water use—how it is used and the quantities required for each sector. If a facility cannot be easily compared with a facility of similar size and sector, knowing if it is effectively using water conservation best practices is difficult. One potential source of industrial water use data is the U.S. Department of Energy (DOE)–sponsored Industrial Assessment Centers (IACs). IACs are university-based organizations that provide free audits to small- and medium-sized manufacturing facilities to identify productivity improvement and waste and energy reduction opportunities. The IACs also maintain a database of all the audits conducted, which currently holds more than 19,267 assessments and 145,000 recommendations (as of July 24, 2020). This database also contains energy utility (electricity, natural gas, and other fuels) and water utility data, making it a potential data source for industrial water use. This report attempts to create regression models to predict a small- or medium-sized industrial facility’s annual water use or cost based on its industrial subsector and several possible relevant variables. Using data collected by IAC assessments, models for several industrial subsectors were generated via stepwise regression techniques to determine which variables (annual sales, number of employees, facility/plant area, annual production hours, and a water stress metric) are relevant.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Assessment of oil and gas fields in California as potential CO 2 storage sites

California's total annual greenhouse gas (GHG) emissions (425.3 MtCO 2 e) in 2018 were about 6.4% of the US total (6,677 MtCO 2 e) and around 1% of global emissions. About 39% of 2018 GHG emissions in California were from the industrial and electrical sectors. Many of these emissions were from large stationary point sources and were suitable for carbon capture retrofit with subsequent storage of the captured carbon dioxide (CO 2 ) in geological formations. Previous studies of California found suitable geology and CO 2 storage resource. This study refines and furthers prior work using a three-stage screening process of oil fields, gas fields, and underground natural gas storage (UGS) sites by combining criteria from previous studies while excluding sites that pose technical risk or are located in regions with surface restrictions including sensitive habitats and dense populations. In the first stage, 129 CO 2 storage sites in California were identified using qualification criteria based upon formation properties including geological conditions and pore pressure. The second stage identified sensitive sites by applying conservative screens including seismic activity, faulting, population density, restricted lands, and sensitive habitats. During the third stage, 61 CO 2 potential storage sites were identified by subtraction of stage 2 areas from stage 1. The potential storage volume in the third stage ranged from 1.0 to 2.0 GtCO 2 . Finally, we applied a scoring system with seven parameters to rank the 61 potential sites based on subsurface technical criteria. The scored sites are classified as high priority, medium priority, and sites for future study. Prospective CO 2 storage sites with high and moderate priority were selected and linked to CO 2 sources. There are 14 prospective sites (above 20 MtCO 2 storage resource per site) with a total storage resource of 1024 MtCO 2 distributed in Northern and Southern California. Of these sites, there are 9 potential CO 2 -EOR sites and 1 depleted oil field with a total estimated CO 2 storage volume of ~800 MtCO 2 in the Southern San Joaquin and Ventura Basin. These 10 prospective sites with a storage resource greater than 20 MtCO 2 could potentially deliver more than 20 years of storage with an average injection rate of 40 MtCO 2 /year. The remaining 4 highly prospective sites are in Northern California. Additionally, study results suggest that saline formations should be re-evaluated in concert with storage in oil, gas, and natural gas storage reservoirs.

58 GEOSCIENCES↗

Statistical upscaling of ecosystem CO 2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties

Abstract The regional variability in tundra and boreal carbon dioxide (CO 2 ) fluxes can be high, complicating efforts to quantify sink‐source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO 2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO 2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high‐latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO 2 fluxes and test the accuracy and uncertainty of different statistical models. CO 2 fluxes were upscaled at relatively high spatial resolution (1 km 2 ) across the high‐latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE‐focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO 2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m −2 yr −1 , respectively) compared to tundra (average annual NEE +10 and −2 g C m −2 yr −1 ). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO 2 budget, estimated using the annual NEE ensemble prediction, suggests the high‐latitude region was on average an annual CO 2 sink during 1990–2015, although uncertainty remains high.

Virkkala, Anna‐Maria↗

Slipstream Testing of Amine-Based Solvents at a Low-Rank Coal-Fired Power Plant

Conference presentation for 38th Annual International Pittsburgh Coal Conference, Virtual, September 20–23, 2021. To better assess mitigation strategies for aerosol reduction to extend solvent life, the University of North Dakota Energy & Environmental Research Center (EERC) installed a pilot-scale CO 2 absorption system at a lignite-fired plant in central North Dakota. The pilot-scale system was operated using both commercial KS-1™ solvent and advanced KS-21™ solvent provided by Mitsubishi Heavy Industries (MHI). MHI’s proprietary amine emission reduction unit (AERU™) technology was installed downstream of the absorber columns to reduce solvent losses by recovering amines at the system outlet. Fine particulate loading was measured throughout the capture system with and without a WESP operating and using both solvents. Captured particulate was brought back to the EERC to be analyzed for chemical composition and to be examined by scanning electron microscopy for particulate structure. These variables were then correlated to performance of particulate control devices in reducing aerosol formation and solvent losses.

01 COAL, LIGNITE, AND PEAT↗

NASA System Safety Handbook: System Safety Framework and Concepts for Implementation - Volume 1

System safety assessment is defined in NPR 8715.3C, NASA General Safety Program Requirements as a disciplined, systematic approach to the analysis of risks resulting from hazards that can affect humans, the environment, and mission assets. Achievement of the highest practicable degree of system safety is one of NASA's highest priorities. Traditionally, system safety assessment at NASA and elsewhere has focused on the application of a set of safety analysis tools to identify safety risks and formulate effective controls.1 Familiar tools used for this purpose include various forms of hazard analyses, failure modes and effects analyses, and probabilistic safety assessment (commonly also referred to as probabilistic risk assessment (PRA)). In the past, it has been assumed that to show that a system is safe, it is sufficient to provide assurance that the process for identifying the hazards has been as comprehensive as possible and that each identified hazard has one or more associated controls. The NASA Aerospace Safety Advisory Panel (ASAP) has made several statements in its annual reports supporting a more holistic approach. In 2006, it recommended that "... a comprehensive risk assessment, communication and acceptance process be implemented to ensure that overall launch risk is considered in an integrated and consistent manner." In 2009, it advocated for "... a process for using a risk-informed design approach to produce a design that is optimally and sufficiently safe." As a rationale for the latter advocacy, it stated that "... the ASAP applauds switching to a performance-based approach because it emphasizes early risk identification to guide designs, thus enabling creative design approaches that might be more efficient, safer, or both." For purposes of this preface, it is worth mentioning three areas where the handbook emphasizes a more holistic type of thinking. First, the handbook takes the position that it is important to not just focus on risk on an individual basis but to consider measures of aggregate safety risk and to ensure wherever possible that there be quantitative measures for evaluating how effective the controls are in reducing these aggregate risks. The term aggregate risk, when used in this handbook, refers to the accumulation of risks from individual scenarios that lead to a shortfall in safety performance at a high level: e.g., an excessively high probability of loss of crew, loss of mission, planetary contamination, etc. Without aggregated quantitative measures such as these, it is not reasonable to expect that safety has been optimized with respect to other technical and programmatic objectives. At the same time, it is fully recognized that not all sources of risk are amenable to precise quantitative analysis and that the use of qualitative approaches and bounding estimates may be appropriate for those risk sources. Second, the handbook stresses the necessity of developing confidence that the controls derived for the purpose of achieving system safety not only handle risks that have been identified and properly characterized but also provide a general, more holistic means for protecting against unidentified or uncharacterized risks. For example, while it is not possible to be assured that all credible causes of risk have been identified, there are defenses that can provide protection against broad categories of risks and thereby increase the chances that individual causes are contained. Third, the handbook strives at all times to treat uncertainties as an integral aspect of risk and as a part of making decisions. The term "uncertainty" here does not refer to an actuarial type of data analysis, but rather to a characterization of our state of knowledge regarding results from logical and physical models that approximate reality. Uncertainty analysis finds how the output parameters of the models are related to plausible variations in the input parameters and in the modeling assumptions. The evaluation of unrtainties represents a method of probabilistic thinking wherein the analyst and decision makers recognize possible outcomes other than the outcome perceived to be "most likely." Without this type of analysis, it is not possible to determine the worth of an analysis product as a basis for making decisions related to safety and mission success. In line with these considerations the handbook does not take a hazard-analysis-centric approach to system safety. Hazard analysis remains a useful tool to facilitate brainstorming but does not substitute for a more holistic approach geared to a comprehensive identification and understanding of individual risk issues and their contributions to aggregate safety risks. The handbook strives to emphasize the importance of identifying the most critical scenarios that contribute to the risk of not meeting the agreed-upon safety objectives and requirements using all appropriate tools (including but not limited to hazard analysis). Thereafter, emphasis shifts to identifying the risk drivers that cause these scenarios to be critical and ensuring that there are controls directed toward preventing or mitigating the risk drivers. To address these and other areas, the handbook advocates a proactive, analytic-deliberative, risk-informed approach to system safety, enabling the integration of system safety activities with systems engineering and risk management processes. It emphasizes how one can systematically provide the necessary evidence to substantiate the claim that a system is safe to within an acceptable risk tolerance, and that safety has been achieved in a cost-effective manner. The methodology discussed in this handbook is part of a systems engineering process and is intended to be integral to the system safety practices being conducted by the NASA safety and mission assurance and systems engineering organizations. The handbook posits that to conclude that a system is adequately safe, it is necessary to consider a set of safety claims that derive from the safety objectives of the organization. The safety claims are developed from a hierarchy of safety objectives and are therefore hierarchical themselves. Assurance that all the claims are true within acceptable risk tolerance limits implies that all of the safety objectives have been satisfied, and therefore that the system is safe. The acceptable risk tolerance limits are provided by the authority who must make the decision whether or not to proceed to the next step in the life cycle. These tolerances are therefore referred to as the decision maker's risk tolerances. In general, the safety claims address two fundamental facets of safety: 1) whether required safety thresholds or goals have been achieved, and 2) whether the safety risk is as low as possible within reasonable impacts on cost, schedule, and performance. The latter facet includes consideration of controls that are collective in nature (i.e., apply generically to broad categories of risks) and thereby provide protection against unidentified or uncharacterized risks.

Dezfuli, Homayoon↗