Trade studies for nuclear space power systems

As human visions of space applications expand and as we probe further out into the universe, our needs for power will also expand, and missions will evolve which are enabled by nuclear power. A broad spectrum of missions which are enhanced or enabled by nuclear power sources have been defined. These include Earth orbital platforms, deep space platforms, planetary exploration, and terrestrial resource exploration. The recently proposed Space Exploration Initiative (SEI) to the Moon and Mars has more clearly defined these missions and their power requirements. Presented here are results of recent studies of radioisotope and nuclear reactor energy sources, combined with various energy conversion devices for Earth orbital applications, SEI lunar/Mars rovers, surface power, and planetary exploration

Magnetohydrodynamics (MHD) Engineering Test Facility (ETF) 200 MWe power plant. Design Requirements Document (DRD)

A description and the design requirements for the 200 MWe (nominal) net output MHD Engineering Test Facility (ETF) Conceptual Design, are presented. Performance requirements for the plant are identified and process conditions are indicated at interface stations between the major systems comprising the plant. Also included are the description, functions, interfaces and requirements for each of these major systems. The lastest information (1980-1981) from the MHD technology program are integrated with elements of a conventional steam electric power generating plant

Design of multihundredwatt DIPS for robotic space missions

Design of a dynamic isotope power system (DIPS) general purpose heat source (GPHS) and small free piston Stirling engine (FPSE) is being pursued as a potential lower cost alternative to radioisotope thermoelectric generators (RTG's). The design is targeted at the power needs of future unmanned deep space and planetary surface exploration missions ranging from scientific probes to SEI precursor missions. These are multihundredwatt missions. The incentive for any dynamic system is that it can save fuel which reduces cost and radiological hazard. However, unlike a conventional DIPS based on turbomachinery converions, the small Stirling DIPS can be advantageously scaled to multihundred watt unit size while preserving size and weight competitiveness with RTG's. Stirling conversion extends the range where dynamic systems are competitive to hundreds of watts (a power range not previously considered for dynamic systems). The challenge of course is to demonstrate reliability similar to RTG experience. Since the competative potential of FPSE as an isotope converter was first identified, work has focused on the feasibility of directly integrating GPHS with the Stirling heater head. Extensive thermal modeling of various radiatively coupled heat source/heater head geometries were performed using data furnished by the developers of FPSE and GPHS. The analysis indicates that, for the 1050 K heater head configurations considered, GPHS fuel clad temperatures remain within safe operating limits under all conditions including shutdown of one engine. Based on these results, preliminary characterizations of multihundred watt units were established

Conceptual design of the MHD Engineering Test Facility

The reference conceptual design of the MHD engineering test facility, a prototype 200 MWe coal-fired electric generating plant designed to demonstrate the commerical feasibility of open cycle MHD is summarized. Main elements of the design are identified and explained, and the rationale behind them is reviewed. Major systems and plant facilities are listed and discussed. Construction cost and schedule estimates are included and the engineering issues that should be reexamined are identified

Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)

Forest cover loss and bare ground gain from 2006 to 2010 for the conterminous United States (CONUS) were quantified at a 30 m spatial resolution using Web-Enabled Landsat Data available from the USGS Center for Earth Resources Observation and Science (EROS) (http://landsat.usgs.gov/WELD.php). The approach related multi-temporal WELD metrics and expert-derived training data for forest cover loss and bare ground gain through a decision tree classification algorithm. Forest cover loss was reported at state and ecoregional scales, and the identification of core forests\u27 absent of change was made and verified using LiDAR data from the GLAS (Geoscience Laser Altimetry System) instrument. Bare ground gain correlated with population change for large metropolitan statistical areas (MSAs) outside of desert or semi-desert environments. Google Earth™ time series images were used to validate the products. Mapped forest cover loss totaled 53,084 km2 and was found to be depicted conservatively, with a user\u27s accuracy of 78% and a producer\u27s accuracy of 68%. Excluding errors of adjacency, user\u27s and producer\u27s accuracies rose to 93% and 89%, respectively. Mapped bare ground gain equaled 5974 km2 and nearly matched the estimated area from the reference (Google Earth™) classification; however, user\u27s (42%) and producer\u27s (49%) accuracies were much less than those of the forest cover loss product. Excluding errors of adjacency, user\u27s and producer\u27s accuracies rose to 62% and 75%, respectively. Compared to recent 2001–2006 USGS National Land Cover Database validation data for forest loss (82% and 30% for respective user\u27s and producer\u27s accuracies) and urban gain (72% and 18% for respective user\u27s and producer\u27s accuracies), results using a single CONUS-scale model with WELD data are promising and point to the potential for national scale operational mapping of key land cover transitions. However, validation results highlighted limitations, some of which can be addressed by improving training data, creating a more robust image feature space, adding contemporaneous Landsat 5 data to the inputs, and modifying definition sets to account for differences in temporal and spatial observational scales. The presented land cover extent and change data are available via the official WELD website (ftp://weldftp.cr.usgs.gov/CONUS_5Y_LandCover/ftp://weldftp.cr.usgs. gov/CONUS_5Y_LandCover/)

Interplay of superexchange and orbital degeneracy in Cr-doped LaMnO3

We report on structural, magnetic and Electron Spin Resonance (ESR) investigations in the manganite system LaMn_{1-x}Cr_{x}O_{3} (x<=0.5). Upon Cr-doping we observe a reduction of the Jahn-Teller distortion yielding less distorted orthorhombic structures. A transition from the Jahn-Teller distorted O' to the pseudocubic O phase occurs between 0.3<x<0.4. A clear connection between this transition and the doping dependence of the magnetic and ESR properties has been observed. The effective moments determined by ESR seem reduced with respect to the spin-only value of both Mn^{3+} and Cr^{3+} ions

Potential impact of annual vaccination with reformulated COVID-19 vaccines: Lessons from the US COVID-19 scenario modeling hub

Background AU Coronavirus Disease 2019 (COVID-19) continues to cause :significant hospitalizations and deaths in the United States. Its continued burden and the impact of annually reformulated vaccines remain unclear. Here, we present projections of COVID-19 hospitalizations and deaths in the United States for the next 2 years under 2 plausible assumptions about immune escape (20% per year and 50% per year) and 3 possible CDC recommendations for the use of annually reformulated vaccines (no recommendation, vaccination for those aged 65 years and over, vaccination for all eligible age groups based on FDA approval). Methods and findings The COVID-19 Scenario Modeling Hub solicited projections of COVID-19 hospitalization and deaths between April 15, 2023 and April 15, 2025 under 6 scenarios representing the intersection of considered levels of immune escape and vaccination. Annually reformulated vaccines are assumed to be 65% effective against symptomatic infection with strains circulating on June 15 of each year and to become available on September 1. Age- and state-specific coverage in recommended groups was assumed to match that seen for the first (fall 2021) COVID-19 booster. State and national projections from 8 modeling teams were ensembled to produce projections for each scenario and expected reductions in disease outcomes due to vaccination over the projection period. From April 15, 2023 to April 15, 2025, COVID-19 is projected to cause annual epidemics peaking November to January. In the most pessimistic scenario (high immune escape, no vaccination recommendation), we project 2.1 million (90% projection interval (PI) [1,438,000, 4,270,000]) hospitalizations and 209,000 (90% PI [139,000, 461,000]) deaths, exceeding pre-pandemic mortality of influenza and pneumonia. In high immune escape scenarios, vaccination of those aged 65+ results in 230,000 (95% confidence interval (CI) [104,000, 355,000]) fewer hospitalizations and 33,000 (95% CI [12,000, 54,000]) fewer deaths, while vaccination of all eligible individuals results in 431,000 (95% CI: 264,000–598,000) fewer hospitalizations and 49,000 (95% CI [29,000, 69,000]) fewer deaths. Conclusions COVID-19 is projected to be a significant public health threat over the coming 2 years. Broad vaccination has the potential to substantially reduce the burden of this disease, saving tens of thousands of lives each year

Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections

Long-term trends in differentiation between regions: Sverdlovsk oblast vs Chelyabinsk oblast

Threats of increased differentiation across regions, which have caused inefficient spatial development, are progressively coming into the scientists’ focus. By and large, a peripheral region is unlikely to take the place of the center. In the Urals1 , the Sverdlovsk oblast has long been the center and stayed ahead of its neighbours in terms of socioeconomic performance. Our previous research revealed a phenomenon called ‘synchronisation of economies’. Accordingly, the Chelyabinsk oblast in many instances repeats the trends of the Sverdlovsk oblast, but remains at the periphery. In this regard, studying the differentiation between the two economies becomes a relevant issue. The research aims to construct long-term trends of differentiation between regions using the case of the Sverdlovsk and Chelyabinsk oblasts. The theories of spatial development, including the theory of cumulative growth, constitute the methodological basis of the research. Applying the methods of statistical comparison and times series analysis, the study interprets the data published by Russia’s Federal State Statistics Service (Rosstat), the Unified Interdepartmental Statistical Information System (UISIS), and generated by FIRA PRO information analytics system (OOO “First Independent Rating Agency”). The author proposes a method for assessing differentiation across regions based on 12 indicators. The findings demonstrate that for 2001–2020, the variation between the regions in terms of GRP per capita (in 2001 prices) has increased, whereas in terms of wages in prices of the same year it decreased. In relation to the outsider region, the Sverdlovsk oblast has kept its position in terms of the real GRP per capita compared to the Chelyabinsk oblast, which is approaching the outsider. At the same time, for 2001–2020, both regions have become closer to the leader. With regard to the real wages, the positions of the regions have nearly equalized, the ‘superiority’ over the outsider has decreased

Medium-term trends in economic and technological development of metals industry regions

Since metals industry regions are dependent on the location of production resources and infrastructure, as well as have highly capital-intensive production, they usually feature a slowly changing industrial and technological structure of production. In line with the hypothesis of the study, the technological structure of the manufacturing industry determines the differences in their economic development. The study aims to explore the medium-term trends and patterns in economic and technological development of the metals industry regions. The methodological basis of the research is the structural dynamic approach to studying regional economic development. The methods include multivariate data analysis and clustering algorithms, time series estimation and correlation analysis. The study uses the data on large and medium-sized enterprises by types of economic activities for 2006–2021 taken from an information and analytics system FIRA PRO. According to the findings, the Chelyabinsk, Sverdlovsk, Lipetsk, Vologda and Tula oblasts are metals industry regions. The identified medium-term trends in their economic development show different dynamics of input and output indicators of production both by all types of economic activities and in metals industry in particular. The study proves that the dynamics of metals industry regions’ development largely depends on technological characteristics of the manufacturing industry. The results of the research contribute to the understanding of the adaptation mechanisms of regions’ industry to the changing conditions of external environment