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At least 217 records · Page 12

Stronger Tropical Cyclone–Induced Ocean Cooling in Near-Coastal Regions Compared to the Open Ocean

Abstract Tropical cyclones (TC) often induce strong mixing in the upper ocean that generates a trail of cooler sea surface temperature (Twake) in their wakes. The Twake can affect TC intensity, so its prediction is important, especially in coastal regions where TCs can make landfall. Coastal Twakes are often more complex than those in the open ocean due to the influences of coastline geometry, highly variable water depth, continental runoff, and shelf processes. Using observational data since 2002, here we show a significantly stronger global mean Twake in coastal regions compared to offshore regions. Temperature stratification is the main driver of stronger coastal Twakes in the North Atlantic and east Pacific. In the northwest Pacific and north Indian Ocean, the differences between coastal and offshore Twakes are smaller due to compensation between TC forcings and ocean stratification. The north Indian Ocean is unique in the Northern Hemisphere because salinity stratification plays a major role on the spatial distribution of Twake. In the South Pacific Ocean, TC intensity and translation speed are crucial for explaining coastal–offshore Twake differences, while ocean stratification and mixed layer depth are more important for the coastal–offshore Twake differences in the south Indian Ocean. These findings suggest that coastal–offshore differences in ocean stratification need to be properly represented in models in order to capture changes in TC-induced ocean cooling as storms approach landfall. Significance Statement Landfalling tropical cyclones (TCs) often cause considerable damage in coastal regions with dense human populations. Understanding TC–ocean interaction and how it differs between coastal and offshore regions can help predict TC intensity prior to landfall. Sea surface cooling after TC passage is an important proxy for TC–ocean interaction. A global evaluation of coastal TC-induced cooling has not been conducted. Using data covering two decades, we show significantly stronger TC-induced surface cooling in coastal regions compared to offshore regions at the global scale and in all basins except the northwest Pacific and north Indian Ocean. The difference is driven mainly by upper-ocean conditions in the North Atlantic, east Pacific, and south Indian Ocean, and by TC characteristics in the South Pacific.

54 ENVIRONMENTAL SCIENCES↗

Comparing Regional Energy Consumption for Direct Drone and Truck Deliveries

Drone delivery, once thought of as fictitious, is becoming a reality with the efforts of both forward-looking enterprises and supportive government policies. This emerging mode of e-commerce delivery raises many concerns. One important concern is the energy efficiency of direct delivery drones compared with conventional delivery trucks at a regional systems level. Here, in this study, we develop and apply methods to quantify the regional energy impacts of drone delivery, then we assess these impacts and compare them with the impacts of truck delivery. To study this problem, we develop an optimization model that determines an optimal set of fulfillment centers (FCs) with variable service capacities that allow drones to make direct e-commerce deliveries. We adopt two drone delivery energy estimation models from the literature and use them as inputs to demonstrate the potential range of energy needs. We also develop another optimization model to account for the energy consumption of diesel trucks (DTs) and battery electric vehicles (BEVs). We test the models using validated simulation data for the Chicago metropolitan area in the U.S. to quantify the energy implications of these three delivery modes. For drone delivery, we further extend our analyses by considering the impact of wind speed and flight patterns. Our results show that direct delivery drones require 15.8% more energy than BEVs on an average windy day, and they need 15% more energy than DTs on a very windy day. We provide essential parameter values for reproducibility and list relevant open problems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Endurance Exercise Performance Is Reduced after 6-h Dives at 1.35 ATA When Breathing 100% Oxygen Compared with Air

ABSTRACT Introduction Long-duration dives on consecutive days reduces muscular performance, potentially affecting military personnel. However, a paucity of data exists on how breathing gases affect endurance performance. This study examined the influence of long-duration diving with different breathing gases on aerobic endurance and handgrip performance. Methods Twenty-three military divers completed a single 6-h dive (single dive [SD]) and five 6-h dives over consecutive days (dive week [DW]) with 30-min cycling intervals using air (AIR,n= 13) or 100% oxygen (OXY,n= 10). Before and after SD and DW, subjects completed a maximum handgrip strength test, a handgrip endurance test at 40% maximal strength, and a time to exhaustion run. Results Handgrip endurance decreased after DW in OXY (SD, 1.9 ± 0.0 vs 1.4 ± 0.3 min) compared with AIR (1.8 ± 0.0 vs 1.8 ± 0.2 min) (P< 0.001). Run time decreased after SD (Pre, 20.7 ± 10.4 min; Post, 16.6 ± 7.6 min;P= 0.039) and DW (Pre, 21.6 ± 9.0 min; Post, 11.2 ± 4.0 min;P< 0.001) in OXY and after overall diving in AIR (Pre, 26.5 ± 10.2 min; Post, 22.3 ± 7.5 min;P= 0.025). V̇O 2 decreased after diving only in AIR (Pre, 42.6 ± 3.4 mL·kg −1 ⋅min −1 ; Post, 40.4 ± 3.7 mL·kg −1 ⋅min −1 ;P= 0.010). There were no other significant effects. Conclusions Breathing 100% oxygen during long-duration dives on consecutive days may exacerbate decreases in aerobic endurance and impairs handgrip endurance compared with air. Additional research is needed to elucidate mechanisms of action and possible mitigation strategies.

Sport Sciences↗

Comparing optical four-flux model results with experimental data obtained by integrating sphere measurements

Four-flux theory is a way to model scattering through multiple layers of a system based on diffuse and collimated properties. When compared with measurement results obtained using an integrating sphere or a goniophotometer, an approximation is often made as the physical instrument cannot separate the collimated component from the diffuse light scattered in the forward direction. This paper tries to clarify the meaning of the word diffuse for the different cases and outlines simple corrections to improve the accuracy when comparing four-flux models and measured data based on sample haze and the geometry of the integrating sphere.

Bilokur, Maryna (ORCID:0000000191839650)↗

Comparative genomic and phenotypic characterization of invasive non-typhoidal Salmonella isolates from Siaya, Kenya

Non-typhoidal Salmonella (NTS) is a major global health concern that often causes bloodstream infections in areas of the world affected by malnutrition and comorbidities such as HIV and malaria. Developing a strategy to control the emergence and spread of highly invasive and antimicrobial resistant NTS isolates requires a comprehensive analysis of epidemiological factors and molecular pathogenesis. Here, we characterize 11 NTS isolates that caused bloodstream infections in pediatric patients in Siaya, Kenya from 2003–2010. Nine isolates were identified as S . Typhimurium sequence type 313 while the other two were S . Enteritidis. Comprehensive genotypic and phenotypic analyses were performed to compare these isolates to those previously identified in sub-Saharan Africa. We identified a S . Typhimurium isolate referred to as UGA14 that displayed novel plasmid, pseudogene and resistance features as compared to other isolates reported from Africa. Notably, UGA14 is able to ferment both lactose and sucrose due to the acquisition of insertion elements on the pKST313 plasmid. These findings show for the first time the co-evolution of plasmid-mediated lactose and sucrose metabolism along with cephalosporin resistance in NTS further elucidating the evolutionary mechanisms of invasive NTS phenotypes. These results further support the use of combined genomic and phenotypic approaches to detect and characterize atypical NTS isolates in order to advance biosurveillance efforts that inform countermeasures aimed at controlling invasive and antimicrobial resistant NTS.

59 BASIC BIOLOGICAL SCIENCES↗

Laboratory strains of Bacillus anthracis lose their ability to rapidly grow and sporulate compared to wildlife outbreak strains

Bacillus anthracis is the causative agent of anthrax in animals and humans. The organism lies in a dormant state in the soil until introduced into an animal via, ingestion, cutaneous inoculation or inhalation. Once in the host, spores germinate into rapidly growing vegetative cells elaborating toxins. When animals die of anthrax, vegetative bacteria sporulate upon nutrient limitation in the carcass or soil while in the presence of air. After release into the soil environment, spores form a localized infectious zone (LIZ) at and around the carcass. Laboratory strains of B. anthracis produce fewer proteins associated with growth and sporulation compared to wild strains isolated from recent zoonotic disease events. We verified wild strains grow more rapidly than lab strains demonstrating a greater responsiveness to nutrient availability. Sporulation was significantly more rapid in these wild strains compared to lab strains, indicating wild strains are able to sporulate faster due to nutrient limitation while laboratory strains have a decrease in the speed at which they utilize nutrients and an increase in time to sporulation. These findings have implications for disease control at the LIZ as well as on the infectious cycle of this dangerous zoonotic pathogen.

59 BASIC BIOLOGICAL SCIENCES↗

Comparative genetics of Enterococcus faecalis intestinal tissue isolates before and after surgery in a rat model of colon anastomosis

We have recently demonstrated that collagenolytic Enterococcus faecalis plays a key and causative role in the pathogenesis of anastomotic leak, an uncommon but potentially lethal complication characterized by disruption of the intestinal wound following segmental removal of the colon (resection) and its reconnection (anastomosis). Here we hypothesized that comparative genetic analysis of E. faecalis isolates present at the anastomotic wound site before and after surgery would shed insight into the mechanisms by which collagenolytic strains are selected for and predominate at sites of anastomotic disruption. Whole genome optical mapping of four pairs of isolates from rat colonic tissue obtained following surgical resection (herein named "pre-op" isolates) and then 6 days later from the anastomotic site (herein named "post-op" isolates) demonstrated that the isolates with higher collagenolytic activity formed a distinct cluster. In order to perform analysis at a deeper level, a single pair of E. faecalis isolates (16A pre-op and 16A post-op) was selected for whole genome sequencing and assembled using a hybrid assembly algorithm. Comparative genomics demonstrated absence of multiple gene clusters, notably a pathogenicity island in the post-op isolate. No differences were found in the fsr-gelE-sprE genes (EF1817-1822) responsible for regulation and production of collagenolytic activity. Analysis of unique genes among the 16A pre-op and post-op isolates revealed the predominance of transporter systems-related genes in the pre-op isolate and phage-related and hydrolytic enzyme-encoding genes in the post-op isolate. Despite genetic differences observed between pre-op and post-op isolates, the precise genetic determinants responsible for their differential expression of collagenolytic activity remains unknown.

59 BASIC BIOLOGICAL SCIENCES↗

Tracking cropland transitions: A comparative analysis of U.S. land cover change data

There are a growing number of land cover data available for the conterminous United States, supporting various applications ranging from biofuel regulatory decisions to habitat conservation assessments. These datasets vary in their source information, frequency of data collection and reporting, land class definitions, categorical detail, and spatial scale and time intervals of representation. These differences limit direct comparison, contribute to disagreements among studies, confuse stakeholders, and hamper our ability to confidently report key land cover trends in the U.S. Here we assess changes in cropland derived from the Land Change Monitoring, Assessment, and Projection (LCMAP) dataset from the U.S. Geological Survey and compare them with analyses of three established land cover datasets across the coterminous U.S. from 2008-2017: (1) the National Resources Inventory (NRI), (2) a dataset Lark et al. 2020 derived from the Cropland Data Layer (CDL), and (3) a dataset from Potapov et al. 2022. LCMAP reports more stable cropland and less stable noncropland in all comparisons, likely due to its more expansive definition of cropland which includes managed grasslands (pasture and hay). Despite these differences, net cropland expansion from all four datasets was comparable (5.18-6.33 million acres), although the geographic extent and type of conversion differed. LCMAP projected the largest cropland expansion in the southern Great Plains, whereas other datasets projected the largest expansion in the northwestern and central Midwest. Most of the pixel-level disagreements (86%) between LCMAP and Lark et al. 2020 were due to definitional differences among datasets, whereas the remainder (14%) were from a variety of causes. Cropland expansion in the LCMAP likely reflects conversions of more natural areas, whereas cropland expansion in other data sources also captures conversion of managed pasture to cropland. The particular research question considered (e.g., habitat versus soil carbon) should influence which data source is more appropriate.

60 APPLIED LIFE SCIENCES↗

Mono-mix strategy enables comparative proteomics of a cross-kingdom microbial symbiosis

Cross-kingdom microbial symbioses, such as those between algae and bacteria, are key players in biogeochemical cycles. The molecular changes during initiation and establishment of symbiosis are of great interest, but quantitatively monitoring such changes can be challenging, particularly when the microorganisms differ greatly in size or are intimately associated. Here, we analyze output from label-free, data-dependent acquisition (DDA) LC-MS/MS proteomics experiments investigating the well-studied interaction between the alga Chlamydomonas reinhardtii and the heterotrophic bacterium Mesorhizobium japonicum. We found that detection of bacterial proteins decreased in coculture by 50% proteome-wide due to the abundance of algal proteins. As a result, standard differential expression analysis led to numerous false-positive reports of significantly downregulated proteins, where it was not possible to distinguish meaningful biological responses to symbiosis from artifacts of the reduced protein detection in coculture relative to monoculture. We show that data normalization alone does not eliminate the impact of altered detection on differential expression analysis of the cross-kingdom symbiosis. We assessed two additional strategies to overcome this methodological artifact inherent to DDA proteomics. In the first, we combined algal and bacterial monocultures at a relative abundance that mimicked the coculture, creating a “mono-mix” control to which the coculture could be compared. This approach enabled comparable detection of bacterial proteins in the coculture and the monoculture control. In the second strategy, we enhanced detection of lowly abundant bacterial proteins by using sample fractionation upstream of LC-MS/MS analysis. When these simple approaches were combined, they allowed for meaningful comparisons of nearly 10,000 algal proteins and over 4,000 bacterial proteins in response to symbiosis by DDA. They successfully recovered expected changes in the bacterial proteome in response to algal coculture, including upregulation of sugar-binding proteins and transporters. They also revealed novel proteomic responses to coculture that guide hypotheses about algal-bacterial interactions.

Dupuis, Sunnyjoy [University of California, Berkel↗

A Comparative Study on Representativeness and Stochastic Efficacy of Miniature Tensile Specimen Testing

Here, in this article, a miniature dog bone tensile coupon design was tested against the existing ASTM standard specimen design. Specimens were prepared from commercially sourced austenitic stainless steel 304 alloy, and a defect-ridden additively manufactured 304L alloy was studied. By utilizing a tensile specimen design that is 1/230th volume of the smallest ASTM E8-04(2016), Standard Test Methods for Tension Testing of Metallic Materials, dog bone specimen, coupled to a digital image correlation (DIC) setup, case studies were performed to compare tensile property measurements and strain field evolution. Whereas yield strength measurements were observed to be similar, post-yield, the ultimate strength measurements and ductility measurements from the miniature specimens were observed to be higher than the ASTM specimen design. Although the strength measurements were comparable, the strain evolution was found to differ in the miniature specimens. Studies to assess effects of varying thickness and defect population were also pursued on the miniature tensile specimen. From the DIC strain field estimations, the peak local strain values at ultimate tensile strength were observed to be increasing with reducing specimen thickness. Testing of defect ridden stainless steel revealed the sensitivity to failure through strain localization and the influence of defect size was captured in the strength measurements.

36 MATERIALS SCIENCE↗

Focused wave interactions with floating structures: a blind comparative study

The paper presents results from the Collaborative Computational Project in Wave Structure Interaction (CCP-WSI) Blind Test Series 2. Without prior access to the physical data, participants, with numerical methods ranging from low-fidelity linear models to fully non-linear Navier-Stokes (NS) solvers, simulate the interaction between focused wave events and two separate, taut-moored, floating structures: a hemispherical-bottomed cylinder and a cylinder with a moonpool. The ‘blind’ numerical predictions for heave, surge, pitch and mooring load, are compared against physical measurements. Dynamic time warping is used to quantify the predictive capability of participating methods. In general, NS solvers and hybrid methods give more accurate predictions; however, heave amplitude is predicted reasonably well by all methods; and a WEC-Sim implementation, with CFD-informed viscous terms, demonstrates comparable predictive capability to even the stronger NS solvers. Large variations in the solutions are observed (even among similar methods), highlighting a need for standardisation in the numerical modelling of WSI problems.

42 ENGINEERING↗

A Comparative Study of Deep Learning Models for Fracture and Pore Space Segmentation in Synthetic Fractured Digital Rocks

This study focuses on the comparative study of deep learning (DL) models for pore space and discrete fracture networks (DFNs) segmentation in synthetic fractured digital rocks, specifically targeting low-permeability rock formations, such as shale and tight sandstones. Accurate characterization of pore space and DFNs is critical for subsequent property analysis and fluid flow modeling. Four DL models, SegNet, U-Net, U-Net-wide, and nested U-Net (i.e., U-Net++), were trained, validated, and tested using synthetic datasets, including input and label image pairs with varying properties. The model performance was assessed regarding pixel-wise metrics, including the F1 score and pixel-wise difference maps. In addition, the physics-based metrics were considered for further analysis, including sample porosity and absolute permeability. Particularly, We first simulated the permeability of porous media containing only pore space and then simulated the permeability of porous media with DFNs added. The difference between these two values is used to quantify the connectivity of segmented DFNs, which is an important parameter for low-permeability rocks. The pixel-wise metrics showed that the nested U-Net model outperformed the rest of the DL models in pore space and DFNs segmentation, with the SegNet model exhibiting the second-best performance. Particularly, nested U-Net enhanced segmentation accuracy for challenging boundary pixels affected by partial volume effects. The U-Net-wide model achieved improved accuracy compared to the U-Net model, which indicated the influence of parameter numbers. Similarly, nested U-Net has the closest match to the ground truth of physics-based metrics, including the porosity of pore space and DFNs, and the permeability difference quantifying the connectivity of DFNs. The findings highlight the effectiveness of DL models, especially the U-Net++ model with nested architecture and redesigned skip connections, in accurately segmenting pore spaces and DFNs, which are crucial for pore-scale fluid flow and transport simulation in low-permeability rocks.

Wang, Hongsheng↗

Comparing machine learning and interpolation methods for loop-level calculations

The need to approximate functions is ubiquitous in science, either due to empirical constraints or high computational cost of accessing the function. In high-energy physics, the precise computation of the scattering cross-section of a process requires the evaluation of computationally intensive integrals. A wide variety of methods in machine learning have been used to tackle this problem, but often the motivation of using one method over another is lacking. Comparing these methods is typically highly dependent on the problem at hand, so we specify to the case where we can evaluate the function a large number of times, after which quick and accurate evaluation can take place. We consider four interpolation and three machine learning techniques and compare their performance on three toy functions, the four-point scalar Passarino-Veltman D_0 D 0 function, and the two-loop self-energy master integral M. We find that in low dimensions (d = 3), traditional interpolation techniques like the Radial Basis Function perform very well, but in higher dimensions (d=5, 6, 9) we find that multi-layer perceptrons (a.k.a neural networks) do not suffer as much from the curse of dimensionality and provide the fastest and most accurate predictions.

97 MATHEMATICS AND COMPUTING↗

Comparative Life Cycle Analysis of Scalable Single-Junction and Tandem Perovskite Solar Cell (PSC) Systems

Efficient, low-cost solar cells based upon perovskites have the potential to transform the US and global energy portfolio and improve energy security if they can be manufactured in an environmentally sustainable manner. However, previous life cycle analyses (LCA) of perovskite solar cells (PSC) used lab recipes to project the environmental impact of industrial PSC production – using materials and processes that may not be representative of industrial productions due to high material waste and complex synthesis – and such studies were limited to a few single-junction technologies. Thus, the goal of this project was threefold: a) to review the most promising for industrial production single-junction and tandem PSC technologies, b) to build life-cycle materials inventories that reflect scalable production of these technologies, and c) to conduct comprehensive life-cycle analysis of these technologies and compare their environmental impact with those of established commercial technologies. In response, this project identified challenges for fabrication transitioning from laboratory to sustainable industrial production, developed life-cycle inventory (LCI) data for scaling to industrial production four promising single-junction and three tandem PSC systems and produced life-cycle-investigations using, as metrics, a complete spectrum of energy, environmental and ecological impact indicators. Special focus was given to the use of lead, silver and indium in PSC. The project used the Life Cycle Assessment (LCA) methodology as standardized by the Society of Environmental Toxicology and Chemistry (SETAC), ISO standards 14040 and 14044, and the International Energy Agency PVPS Task 12 LCA guidelines. LCA allows the calculation of a number of energy and environmental and impact categories, including energy cumulative energy demand (CED), global warming potential (GWP), human toxicity potential (HTP), eco-toxicity potential (ETP), abiotic resource depletion potential (ADP), acidification potential (AP), ozone depletion potential (ODP), photochemical oxidation potential (POP), eutrophication potential (EP). In addition to those, we calculated the Energy Pay-Back Time (EPBT) and the Energy Return On Investment (EROI). We provide LCA impacts for complete perovskite PV systems – including balance of system components – installed at three irradiation levels and considering reference and future potential module efficiencies. Finally, a sensitivity analysis on perovskite lifetime has been performed, considering 10, 20 and 30 years. Contribution analysis of the impacts of each material and layer of PSC shows, that the use of Pb in metalorganic PSC does not result in significant environmental impacts as the major contributions to environmental indicators arise from the use of Ag and encapsulation materials. Solution-based PSC manufacturing was found to be less impactful to the environment than vapor-based fabrication, and roll-to-roll (RtR) printing uses less energy and generates the lowest emissions. PSC produced with RtR manufacturing could reach the same Energy Return on Energy Investment (EROI) as that of crystalline-Si PV within 12 years of life, whereas the most energy demanding spray coating on rigid substrates, would require a 20-yr life to match the EROI of 30-yr lasting silicon PV. This work lays the foundation for sustainability investigations in a comparative context of large-scale production and deployment of PSC. The results of this project have the potential to have a significant impact on the future of PV manufacturing, by providing industry, policy-makers, and academia with insights necessary to choose which, if any, lead-based solar cell life cycles are environmentally sustainable.

14 SOLAR ENERGY↗

Comparing Retrofit Wall Performance Predicted from Hygrothermal Simulations to Measurements

Over the past few years ORNL has been showing that WUFI® can be used to predict the moisture performance of walls when exposed to diffusion of water vapor, convection of moist air through the wall, and solar driven moisture. This is accomplished by comparing the hygrothermal simulation results to carefully instruments walls exposed to these phenomena in a climate chamber. In FY 2018, three stick-built walls were succumbed to typical Chicago, Illinois weather conditions in Oak Ridge National Laboratory’s Heat, Air and Moisture chamber. The measured temperature, relative humidity, and moisture content within these walls were compared with WUFI hygrothermal simulation results. In FY 2019, similar experiments and comparisons with WUFI results were completed with two walls, a structural insulated panel-based wall and a concrete masonry unit-based wall. In FY 2020, experiments were completed for a probable exterior retrofit of a wall which included adding cavity and continuous insulation. Two pairs of walls were tested by exposing them to Chicago winter weather with a positive pressure pushing outside air into the wall. The results from the FY 2020 experiments are reported here.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Comparative Assessment of Data-driven Process Models in Health Information Technology

Process mining for conformance analysis consists of comparing a reference process model against a data-driven process model generated via log files from information technology systems. However, in the absence of a complete reference process model, we found no suggested approaches in the literature to address the need for evaluating process conformance among different healthcare facilities to assess standardization of care. Our goal is to find similarities and dissimilarities in data-driven process models among US Veterans Health Administration (VHA) facilities that can be indicative of patient safety issues. Our hypothesis was that the analysis would not produce statistically significant differences in outcome. We present a unique implementation of conformance analysis in process mining that consists of combining process mining, process mapping and statistical metrics. We illustrate our approach by applying it to the analysis of two clinical radiology order process models generated from healthcare data provided by two similar facilities in the VHA. The comparative assessment showed that about 70% of the orders completed successfully and 30% were not completed due to policy and duplications. Our analysis found a good statistical correlation between both facilities, as the Spearman’s correlation coefficient between facilities for the frequency of cases per total hours was 0.87879, for the frequency of cases by state transition was 0.79702 and for the throughput time per state transition was 0.63582. Additional statistical analyses using the Mann-Whitney U test and the root mean square error both produced values that were not significant. The foregoing approach validated our hypothesis by demonstrating a good statistical correlation of data describing the flow of clinical radiology orders absent a credible reference model. Finding good agreement between both facilities was important in confirming that the clinical orders flow in a similar manner, suggesting standardization of care.

97 MATHEMATICS AND COMPUTING↗

Visualization Tool for Comparing Low-Carbon Energy Options

This project developed a web based visualization tool for comparing current and future nuclear fuel cycle options to low-carbon and conventional energy technologies in the United States. While nuclear power is well established as the gold-standard for baseload power production and also as the technology with the lowest overall carbon intensity of any commercial form of electricity generation. This project develop a web-based tool for electricity producers and consumers to compare renewable and conventional energy technologies to the conventional and advanced nuclear fuel cycle options. The work leveraged data on land use, carbon intensity, unit cost and pricing data for renewables from the open literature. Input data from the Advanced Fuel Cycle Cost Basis report will be used for current and advanced nuclear power systems. We coupled these data to energy flow and lifecycle models for user-selected energy generation and storage types. We will display economic comparisons from the perspectives of generators and consumers, as well as carbon production, land use, and reliability comparisons.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗