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At least 163 records · Page 9

2023 Artemis Crew Health and Performance (CHP) System Model Development

While the NASA Human Research Program (HRP) utilizes a Crew Health and Performance (CHP) System to represent all the Agency’s efforts to ensure the health and performance of NASA astronauts, there is no shared mental model of a CHP system at NASA. Some groups may consider a CHP system to be only a medical kit, while others may not be using the concept at all. To facilitate the integration of functions and capabilities to ensure astronaut health and performance during vehicle development, HRP has proposed a CHP Shared Mental Model derived from the NASA Human Health, Medical, and Performance Spaceflight Standards (NASA-STD-3001 Vol.1/Vol.2). [1] Even though many vehicle, ground, and communication systems as well as mission operations are modeled for the Artemis Campaigns, no mission level CHP system model was created to achieve the intent of the HRP CHP Shared Mental Model. The lack of this model renders it difficult to visualize and understand how the many programs work together to provide the necessary cross program functions and capabilities to ensure the health and performance of the crew throughout an Artemis mission. For this purpose, the Exploration Medical Capability (ExMC) element of HRP developed a CHP system model for the Artemis III and IV missions to provide a view of how each program contributes to and interacts with the overall CHP system. To develop the 2023 Artemis CHP system model, ExMC leveraged existing data and models from the Moon to Mars Program Office, the Office of the Chief Health and Medical Officer (OCHMO) and the Orion, Gateway, Extravehicular Activity and Human Surface Mobility (EHP) and Human Landing System (HLS) programs. By using a Model-Based Systems Engineering (MBSE) approach, existing requirements, functions, and concepts of operations were combined to create a single system model focused on representing CHP from the launch to the return to Earth segments of the Artemis III and IV missions. Additionally, by incorporating the HRP Systems Platform for Aggregating and Relating Capabilities, or SPARC tool, the data from the programs was also related back to the 2nd volume of the NASA Human Health, Medical, and Performance Spaceflight Standard (NASA-STD-3001, Vol.2) and the human system risks identified by the Human System Risk Board (HSRB). The first version of the 2023 Artemis CHP system model was baselined in Fall of 2023 after the model was demonstrated to be a potentially useful tool for systems engineers integrating CHP capabilities in vehicle development as well as members of the Health and Medical Technical Authority providing oversight of those programs. The model may also be useful to any stakeholder of astronaut health and performance by providing insights on how an Artemis mission satisfies the NASA Human Health, Medical, and Performance Spaceflight Standards as well as how they mitigate the HSRB Human System Risks. This presentation highlights how the model was developed and the possible benefits of the model. [1] NASA HRP (2022), Crew Health and Performance System Whitepaper

Systems engineering↗

Rapid fluctuations in solar flares

Study of rapid fluctuations in the emission of radiation from solar flares provides a promising approach for probing the magneto-plasma structure and plasma processes that are responsible for a flare. It is proposed that elementary flare bursts in X-ray and microwave emission may be attributed to fine structure of the coronal magnetic field, related to the aggregation of photospheric magnetic field into magnetic knots. Fluctuations that occur on a subsecond time-scale may be due to magnetic islands that develop in current sheets during magnetic reconnection. The impulsive phase may sometimes represent the superposition of a large number of the elementary energy-release processes responsible for elementary flare bursts. If so, the challenge of trying to explain the properties of the impulsive phase in terms of the properties of the elementary processes must be faced. Magnetic field configurations that might produce solar flares are divided into a number of categories, depending on: whether or not there is a filament; whether there is no current sheet, a closed current sheet, or an open current sheet; and whether the filament erupts into the corona, or is ejected completely from the Sun's atmosphere. Analysis of the properties of these possible configurations is compared with different types of flares, and to Bai's subdivision of gamma-ray/proton events.

Sturrock, Peter A.↗

The Averaged Face Growth Rates of lysozyme Crystals: The Effect of Temperature

Measurements of the averaged or macroscopic face growth rates of lysozyme crystals are reported here for the (110) face of tetragonal lysozyme, at three sets of pH and salt concentrations, with temperatures over a 4-22 C range for several protein concentrations. The growth rate trends with supersaturation were similar to previous microscopic growth rate measurements. However, it was found that at high super-saturations the growth rates attain a maximum and then start decreasing. No 'dead zone' was observed but the growth rates were found to approach zero asymptotically at very low super-saturations. The growth rate data also displayed a dependence on pH and salt concentration which could not be characterized solely by the super-saturation. A complete mechanism for lysozyme crystal growth, involving the formation of an aggregate growth unit, mass transport of the growth unit to the crystal interface and faceted crystal growth by growth unit addition, is suggested. Such a mechanism may provide a more consistent explanation for the observed growth rate trends than those suggested by other investigators. The nutrient solution interactions leading to the formation of the aggregate growth unit may, thus, be as important as those occurring at the crystal interface and may account for the differences between small molecule and protein crystal growth.

Nadarajah, Arunan↗

Crowd Sourcing Approach for UAS Communication Resource Demand Forecasting

Congressional attention to Unmanned Aircraft Systems (UAS) has caused the Federal Aviation Administration (FAA) to move the National Airspace System (NAS) Integration project forward, but using guidelines, practices and procedures that are yet to be fully integrated with the FAA Aviation Management System. The real drive for change in the NAS will to come from both UAS operators and the government jointly seeing an accurate forecast of UAS usage demand data. This solid forecast information would truly get the attention of planners. This requires not an aggregate demand, but rather a picture of how the demand is spread across small to large UAS, how it is spread across a wide range of missions, how it is expected over time and where, in terms of geospatial locations, will the demand appear. In 2012 the Volpe Center performed a study of the overall future demand for UAS. This was done by aggregate classes of aircraft types. However, the realistic expected demand will appear in clusters of aircraft activities grouped by similar missions on a smaller geographical footprint and then growing from those small cells. In general, there is not a demand forecast that is tightly coupled to the real purpose of the mission requirements (e.g. in terms of real locations and physical structures such as wind mills to inspect, farms to survey, pipelines to patrol, etc.). Being able to present a solid basis for the demand is crucial to getting the attention of investment, government and other fiscal planners. To this end, Mosaic ATM under NASA guidance is developing a crowd sourced, demand forecast engine that can draw forecast details from commercial and government users and vendors. These forecasts will be vetted by a governance panel and then provide for a sharable accurate set of projection data. Our paper describes the project and the technical approach we are using to design and create access for users to the forecast system.

air traffic↗

Algorithms for Automatic Alignment of Arrays

Aggregate data objects (such as arrays) are distributed across the processor memories when compiling a data-parallel language for a distributed-memory machine. The mapping determines the amount of communication needed to bring operands of parallel operations into alignment with each other. A common approach is to break the mapping into two stages: an alignment that maps all the objects to an abstract template, followed by a distribution that maps the template to the processors. This paper describes algorithms for solving the various facets of the alignment problem: axis and stride alignment, static and mobile offset alignment, and replication labeling. We show that optimal axis and stride alignment is NP-complete for general program graphs, and give a heuristic method that can explore the space of possible solutions in a number of ways. We show that some of these strategies can give better solutions than a simple greedy approach proposed earlier. We also show how local graph contractions can reduce the size of the problem significantly without changing the best solution. This allows more complex and effective heuristics to be used. We show how to model the static offset alignment problem using linear programming, and we show that loop-dependent mobile offset alignment is sometimes necessary for optimum performance. We describe an algorithm with for determining mobile alignments for objects within do loops. We also identify situations in which replicated alignment is either required by the program itself or can be used to improve performance. We describe an algorithm based on network flow that replicates objects so as to minimize the total amount of broadcast communication in replication.

Chatterjee, Siddhartha↗

Argument-Based Airworthiness Assurance of Small UAS

Presently, there are three avenues by which Unmanned Aircraft System (UAS) operations are authorized in the U.S. National Airspace System (NAS): obtaining either (i) a certificate of authorization (COA), or (ii) a special airworthiness certificate (SAC) in either the experimental, or the restricted category, or (iii) an exemption from an airworthiness certificate together with a civil COA. The first is meant primarily for public entities, such as NASA; the remaining two are the only available means for civil UAS operations. Recently, the Federal Aviation Administration (FAA) has also proposed a regulatory framework targeted for certain small UAS, specifically those weighing 55 pounds or less, although final rulemaking remains pending. We have previously shown how an assurance case can aggregate heterogeneous reasoning and safety evidence, with application to UAS safety. In this paper, we describe how assurance cases can serve as a common framework to justify overall system safety, unifying both operational aspects and airworthiness, in particular system design assurance. We also show how this approach can coexist with, and augment, existing safety analysis processes and best-practices, by transforming the artifacts they produce into structured assurance arguments. To illustrate the applicability and utility of our approach, we have been applying it for the design assurance of an unmanned rotorcraft system, intended for precision agriculture operations, as part of the NASA Unmanned Aircraft System (UAS) Integration in the National Airspace System (NAS) project.

Rotocraft↗

Passenger Aggregation Network with Very Efficient Listing (PANVEL) Ridesharing Model for Urban Air Mobility

This paper introduces a ridesharing model useful for examining the role of ridesharing in advancing Urban Air Mobility (UAM) operations. Although the success of UAM will likely require a host of new technologies in aircraft design, airspace management, autonomy, and more, operational innovations like ridesharing may also be key, especially to lower operating costs and attract a broader market. The ridesharing algorithm introduced, termed the Passenger Aggregation Network with Very Efficient Listing (PANVEL) model, estimates trip numbers and passenger occupancy aboard particular aircraft within a UAM network in a metropolitan area. This algorithm is applied within a transportation computational framework to determine the impact of ridesharing on mode choice, passenger travel patterns, and transportation costs. The algorithm aggregates passengers traveling between identical origin-destination pairs, factoring in individual-specific metrics, such as value of time and alternative mode options, to generate high load factors on UAM aircraft. The computational framework simulates passenger mode-choice selections using an effective-cost approach to determine the number of ridesharing UAM-preferred trips, and results with ridesharing are representative of a rough upper bound on UAM ridership potential for a given metro area. A case study in the Cleveland metro area is presented to demonstrate the algorithm and assess ridesharing potential.

advanced air mobility↗

Passenger Aggregation Network with Very Efficient Listing (PANVEL) Ridesharing Model for Urban Air Mobility

This presentation introduces a ridesharing model useful for examining the role of ridesharing in advancing Urban Air Mobility (UAM) operations. Although the success of UAM will likely require a host of new technologies in aircraft design, airspace management, autonomy, and more, operational innovations like ridesharing may also be key, especially to lower operating costs and attract a broader market. The ridesharing algorithm introduced, termed the Passenger Aggregation Network with Very Efficient Listing (PANVEL) model, estimates trip numbers and passenger occupancy aboard particular aircraft within a UAM network in a metropolitan area. This algorithm is applied within a transportation computational framework to determine the impact of ridesharing on mode choice, passenger travel patterns, and transportation costs. The algorithm aggregates passengers traveling between identical origin-destination pairs, factoring in individual-specific metrics, such as value of time and alternative mode options, to generate high load factors on UAM aircraft. The computational framework simulates passenger mode-choice selections using an effective-cost approach to determine the number of ridesharing UAM-preferred trips, and results with ridesharing are representative of a rough upper bound on UAM ridership potential for a given metro area. A case study in the Cleveland metro area is presented to demonstrate the algorithm and assess ridesharing potential.

advanced air mobility↗

Evaluating Nighttime CALIOP 0.532 micron Aerosol Optical Depth and Extinction Coefficient Retrievals

NASA Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) Version 3.01 5-km nighttime 0.532 micron aerosol optical depth (AOD) datasets from 2007 are screened, averaged and evaluated at 1 deg X 1 deg resolution versus corresponding/co-incident 0.550 micron AOD derived using the US Navy Aerosol Analysis and Prediction System (NAAPS), featuring two-dimensional variational assimilation of quality-assured NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) AOD. In the absence of sunlight, since passive radiometric AOD retrievals rely overwhelmingly on scattered radiances, the model represents one of the few practical global estimates available from which to attempt such a validation. Daytime comparisons, though, provide useful context. Regional-mean CALIOP vertical profiles of night/day 0.532 micron extinction coefficient are compared with 0.523/0.532 micron ground-based lidar measurements to investigate representativeness and diurnal variability. In this analysis, mean nighttime CALIOP AOD are mostly lower than daytime (0.121 vs. 0.126 for all aggregated data points, and 0.099 vs. 0.102 when averaged globally per normalised 1 deg. X 1 deg. bin), though the relationship is reversed over land and coastal regions when the data are averaged per normalised bin (0.134/0.108 vs. 0140/0.112, respectively). Offsets assessed within single bins alone approach +/- 20 %. CALIOP AOD, both day and night, are higher than NAAPS over land (0.137 vs. 0.124) and equal over water (0.082 vs. 0.083) when averaged globally per normalised bin. However, for all data points inclusive, NAAPS exceeds CALIOP over land, coast and ocean, both day and night. Again, differences assessed within single bins approach 50% in extreme cases. Correlation between CALIOP and NAAPS AOD is comparable during both day and night. Higher correlation is found nearest the equator, both as a function of sample size and relative signal magnitudes inherent at these latitudes. Root mean square deviation between CALIOP and NAAPS varies between 0.1 and 0.3 globally during both day/night. Averaging of CALIOP along-track AOD data points within a single NAAPS grid bin improves correlation and RMSD, though day/night and land/ocean biases persist and are believed systematic. Vertical profiles of extinction coefficient derived in the Caribbean compare well with ground-based lidar observations, though potentially anomalous selection of a priori lidar ratios for CALIOP retrievals is likely inducing some discrepancies. Mean effective aerosol layer top heights are stable between day and night, indicating consistent layer-identification diurnally, which is noteworthy considering the potential limiting effects of ambient solar noise during day.

aerosol optical depth↗

On the Convergence of Numerical Computations for Both Exact and Approximate Solutions for Electromagnetic Scattering by Nonspherical Dielectric Particles

We summarize the size parameter range of the applicability of four lightscattering computational methods for nonspheric dielectric particles. These methods include two exact methods - the extended boundary condition method (EBCM) and the invariant imbedding T-matrix method (II-TM) and two approximate approaches - the physical-geometric optics method (PGOM) and the improved geometric optics method (IGOM). For spheroids, the single-scattering properties computed by EBCM and II-TM agree for size parameters up to 150, and the comparison gives us confidence in using IITM as a benchmark for size parameters up to 150 for other geometries (e.g., hexagonal columns) because the applicability of II-TM with respect to particle shape is generic, as demonstrated in our previous studies involving a complex aggregate. This study demonstrates the convergence of the exact II-TM and approximate PGOM solutions for the complete set of single-scattering properties of a nonspherical shape other than spheroids and circular cylinders with particle sizes of ~48λ, specifically a hexagonal column with a size parameter of length as kL=300, where k=2π/λ and L is the column length. IGOM is also quite accurate except near the exact 180º backscattering direction. This study demonstrates that a synergetic combination of the numerically-exact II-TM and the approximate PGOM can seamlessly cover the entire size parameter range of practical interest. To demonstrate the applicability of the approach, we compute the optical properties of dust particles with a downstream application to the retrieval of dust aerosol optical thickness and effective particle size from polarimetric observations.

Ping Yang↗

The crop assessment subsystem: System implementation and approaches used for the generation of crop production reports

The primary responsibility of the crop assessment subsystem (CAS) during the three phases of LACIE was to produce crop reports that included estimates of wheat area, yield, and production, as well as a specified set of associated statistical descriptors. The operations of CAS are described with emphasis on sampling strategy, input/output data, evolution of aggregation/reporting system capabilities, and CAS aggregation procedures.

Mcallum, W. E.↗

A superior edge preserving filter with a systematic analysis

A new, adaptive, edge preserving filter for use in image processing is presented. It had superior performance when compared to other filters. Termed the contiguous K-average, it aggregates pixels by examining all pixels contiguous to an existing cluster and adding the pixel closest to the mean of the existing cluster. The process is iterated until K pixels were accumulated. Rather than simply compare the visual results of processing with this operator to other filters, some approaches were developed which allow quantitative evaluation of how well and filter performs. Particular attention is given to the standard deviation of noise within a feature and the stability of imagery under iterative processing. Demonstrations illustrate the performance of several filters to discriminate against noise and retain edges, the effect of filtering as a preprocessing step, and the utility of the contiguous K-average filter when used with remote sensing data.

Holladay, Kenneth W.↗

Level-Set Topology Optimization with Aeroelastic Constraints

Level-set topology optimization is used to design a wing considering skin buckling under static aeroelastic trim loading, as well as dynamic aeroelastic stability (flutter). The level-set function is defined over the entire 3D volume of a transport aircraft wing box. Therefore, the approach is not limited by any predefined structure and can explore novel configurations. The Sequential Linear Programming (SLP) level-set method is used to solve the constrained optimization problems. The proposed method is demonstrated using three problems with mass, linear buckling and flutter objective and/or constraints. A constraint aggregation method is used to handle multiple buckling constraints in the wing skins. A continuous flutter constraint formulation is used to handle difficulties arising from discontinuities in the design space caused by a switching of the critical flutter mode.

Dunning, Peter D.↗

Preliminary Work in Obtaining Site-Directed Mutants of Hen Egg White Lysozyme

Protein crystal growth studies are recognized as a critical endeavor in the field of molecular biotechnology. The scientific applications of this field include the understanding of how enzymes function and the accumulation of accurate information of atomic structures, a key factor in the process of rational drug design. NASA has committed substantial investment and resources to the field of protein crystal growth and has conducted many microgravity protein crystal growth experiments aboard shuttle flights. Crystals grown in space tend to be larger, denser and have a more perfect habit and geometry. These improved properties gained in the microgravity environment of space result largely from the reduction of solutal convection, and the elimination of sedimentation at the growing crystal surface. Shuttle experiments have yielded many large, high quality crystals that are suitable for high resolution X-ray diffraction analysis. Examples of biologically important macromolecules which have been successfully crystallized during shuttle missions include: lysozyme, isocitrate lyase, gamma-interferon, insulin, human serum albumin and canavalin. Numerous other examples are also available. In addition to obtaining high quality crystals, investigators are also interested in learning the mechanisms by which the growth events take place. Crystallization experiments indicate that for the enzyme HEWL, measured growth rates do not follow mathematical models for 2D nucleation and dislocation-led growth of tetragonal protein crystals. As has been suggested by the laboratory of Marc L. Pusey, a possible explanation for the disagreement between observation and data is that HEWL tetraconal crystals form by aggregated units of lysozyme in supersaturated solutions. Surface measurement data was shown to fit very well with a model using an octamer unit cell as the growth unit. According to this model, the aggregation pathway and subsequent crystal growth is described by: monomer < ------ > dimer < ------- > tetramer < ------ > octamer < ------ > higher order. It is believed that multimer aggregation of lysozyme occurs by interaction at specific binding sites on the surface of the protein crystals. If the presence of discrete binding sites and the aggregation hypothesis is true, then it follows that the alteration of the binding site(s) should have significant effect on the measurements obtained during growth experiments. Site-directed mutagenesis allows the specific alteration of proteins by replacement, deletion or addition of specific amino acid residues. This report outlines the approach for this strategy and the progress made thus far toward that end.

Holmes, Leonard D.↗

Contribution of Small-Scale Correlated Fluctuations of Microstructural Properties of a Spatially Extended Geophysical Target Under the Assessment of Radar Backscatter

The study of the collective effects of radar scattering from an aggregation of discrete scatterers randomly distributed in a space is important for better understanding the origin of the backscatter from spatially extended geophysical targets (SEGT). We consider the microstructure irregularities of a SEGT as the essential factor that affect radar backscatter. To evaluate their contribution this study uses the "slice" approach: particles close to the front of incident radar wave are considered to reflect incident electromagnetic wave coherently. The radar equation for a SEGT is derived. The equation includes contributions to the total backscatter from correlated small-scale fluctuations of the slice's reflectivity. The correlation contribution changes in accordance with an earlier proposed idea by Smith (1964) based on physical consideration. The slice approach applied allows parameterizing the features of the SEGT's inhomogeneities.

Yurchak, Boris S.↗

The Experience Factory: Strategy and Practice

The quality movement, that has had in recent years a dramatic impact on all industrial sectors, has recently reached the system and software industry. Although some concepts of quality management, originally developed for other product types, can be applied to software, its specificity as a product which is developed and not produced requires a special approach. This paper introduces a quality paradigm specifically tailored on the problem of the systems and software industry. Reuse of products, processes and experiences originating from the system life cycle is seen today as a feasible solution to the problem of developing higher quality systems at a lower cost. In fact, quality improvement is very often achieved by defining and developing an appropriate set of strategic capabilities and core competencies to support them. A strategic capability is, in this context, a corporate goal defined by the business position of the organization and implemented by key business processes. Strategic capabilities are supported by core competencies, which are aggregate technologies tailored to the specific needs of the organization in performing the needed business processes. Core competencies are non-transitional, have a consistent evolution, and are typically fueled by multiple technologies. Their selection and development requires commitment, investment and leadership. The paradigm introduced in this paper for developing core competencies is the Quality Improvement Paradigm which consists of six steps: (1) Characterize the environment, (2) Set the goals, (3) Choose the process, (4) Execute the process, (5) Analyze the process data, and (6) Package experience. The process must be supported by a goal oriented approach to measurement and control, and an organizational infrastructure, called Experience Factory. The Experience Factory is a logical and physical organization distinct from the project organizations it supports. Its goal is development and support of core competencies through capitalization and reuse of its cycle experience and products. The paper introduces the major concepts of the proposed approach, discusses their relationship with other approaches used in the industry, and presents a case in which those concepts have been successfully applied.

Basili, Victor R.↗

An Internal Thermal Environment Model of an Aluminized Solid Rocket Motor with Experimental Validation

Due to the severity of the internal solid rocket motor (SRM) environment, very few direct measurements of that environment exist; therefore, the appearance of such data provides a unique opportunity to assess current thermal/fluid modeling capabilities. As part of a previous study of SRM internal insulation performance, the internal thermal environment of a laboratory-scale SRM featuring aluminized propellant was characterized with two types of custom heat-flux calorimeters: one that measured the total heat flux to a graphite slab within the SRM chamber and another that measured the thermal radiation flux. Therefore, in the current study, a thermal/fluid model of this lab-scale SRM was constructed using ANSYS Fluent to predict not only the flow field structure within the SRM and the convective heat transfer to the interior walls, but also the resulting dispersion of alumina droplets and the radiative heat transfer to the interior walls. The dispersion of alumina droplets within the SRM chamber was determined by employing the Lagrangian discrete phase model that was fully coupled to the Eulerian gas-phase flow. The P1-approximation was engaged to model the radiative heat transfer through the SRM chamber where the radiative contributions of the gas phase were ignored and the aggregate radiative properties of the alumina dispersion were computed from the radiative properties of its individual constituent droplets, which were sourced from literature. The convective and radiative heat fluxes computed from the thermal/fluid model were then compared with those measured in the lab-scale SRM test firings and the modeling approach evaluated.

Martin, Heath T.↗

Future Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health over the Coterminous U.S.

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km), to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wideranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S

Quattrochi, Dale A.↗