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At least 1,423 records · Page 79

The Role of Functionalized Conducting Polymer Binders in Improving Power Density and Cycle Life of Lithium-Sulfur Batteries

Lithium-Sulfur batteries are promising as the next-generation of low-cost, high-energy rechargeable batteries. However, the commercialization of this battery has been limited by poor rate capability and cycle life. To improve the performance of Li-S cells, we have investigated the role of two n-dopable conducting polymers, N2200 and N2200-OE, as binders for the sulfur cathode. The electron and ion transport properties of these polymer binders, along with their strong affinity for polysulfides, results in significantly enhanced performance compared to cells with the traditional insulating PVDF binder. The role of these conducting polymer binders in enhancing the performance of the cells is analyzed using impedance spectroscopy, shuttle current measurements, conductivity measurements, UV–vis spectroscopy, GIWAXS studies and post-cycling analysis of the anodes. The conducting polymer binders reduce the cell impedance by a factor of four leading to a marked improvement in rate capability. The shuttling of the polysulfides and the formation of insoluble sulfides at the anode is curtailed by the interaction of the polysulfides with the backbone of the polymer binders, leading to an impressive capacity retention of 82% after 500 cycles. These studies demonstrate the benefit of tailored polymer binders at the sulfur electrode in addressing the limitations of lithium-sulfur batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of the Mathematics of Learning Curve Models for Evaluating Small Modular Reactor Economics

The cost of nuclear power is a straightforward yet complicated topic. It is straightforward in that the cost of nuclear power is a function of the cost to build the nuclear power plant, the cost to operate and maintain it, and the cost to provide fuel for it. It is complicated in that some of those costs are not necessarily known, introducing uncertainty into the analysis. For large light water reactor (LWR)-based nuclear power plants, the uncertainty is mainly contained within the cost of construction. The typical costs of operations and maintenance (O&M), as well as fuel, are well known based on the current fleet of LWRs. However, the last currently operating reactor to come online was Watts Bar 1 in May 1996; thus, the expected construction costs for gigawatt (GW)-class reactors in the United States are based on information nearly two decades old. Extrapolating construction, O&M, and fuel costs from GW-class LWRs to LWR-based small modular reactors (SMRs) introduces even more complication. The per-installed-kilowatt construction costs for SMRs are likely to be higher than those for the GW-class reactors based on the property of the economy of scale. Generally speaking, the economy of scale is the tendency for overall costs to increase slower than the overall production capacity. For power plants, this means that doubling the power production capacity would be expected to cost less than twice as much. Applying this property in the opposite direction, halving the power production capacity would be expected to cost more than half as much. This can potentially make the SMRs less competitive in the electricity market against the GW-class reactors, as well as against other power sources such as natural gas and subsidized renewables. One factor that can potentially aid the SMRs in achieving economic competitiveness is an economy of numbers, as opposed to the economy of scale, associated with learning curves. The basic concept of the learning curve is that the more a new process is repeated, the more efficient the process can be made. Assuming that efficiency directly relates to cost means that the more a new process is repeated successfully and efficiently, the less costly the process can be made. This factor ties directly into the factory fabrication and modularization aspect of the SMR paradigm—manufacturing serial, standardized, identical components for use in nuclear power plants can allow the SMR industry to use the learning curves to predict and optimize deployment costs.

small modular reactors (SMRs)↗

Development of the Mathematics of Learning Curve Models for Evaluating Small Modular Reactor Economics

The cost of nuclear power is a straightforward yet complicated topic. It is straightforward in that the cost of nuclear power is a function of the cost to build the nuclear power plant, the cost to operate and maintain it, and the cost to provide fuel for it. It is complicated in that some of those costs are not necessarily known, introducing uncertainty into the analysis. For large light water reactor (LWR)-based nuclear power plants, the uncertainty is mainly contained within the cost of construction. The typical costs of operations and maintenance (O&M), as well as fuel, are well known based on the current fleet of LWRs. However, the last currently operating reactor to come online was Watts Bar 1 in May 1996; thus, the expected construction costs for gigawatt (GW)-class reactors in the United States are based on information nearly two decades old. Extrapolating construction, O&M, and fuel costs from GW-class LWRs to LWR-based small modular reactors (SMRs) introduces even more complication. The per-installed-kilowatt construction costs for SMRs are likely to be higher than those for the GW-class reactors based on the property of the economy of scale. Generally speaking, the economy of scale is the tendency for overall costs to increase slower than the overall production capacity. For power plants, this means that doubling the power production capacity would be expected to cost less than twice as much. Applying this property in the opposite direction, halving the power production capacity would be expected to cost more than half as much. This can potentially make the SMRs less competitive in the electricity market against the GW-class reactors, as well as against other power sources such as natural gas and subsidized renewables. One factor that can potentially aid the SMRs in achieving economic competitiveness is an economy of numbers, as opposed to the economy of scale, associated with learning curves. The basic concept of the learning curve is that the more a new process is repeated, the more efficient the process can be made. Assuming that efficiency directly relates to cost means that the more a new process is repeated successfully and efficiently, the less costly the process can be made. This factor ties directly into the factory fabrication and modularization aspect of the SMR paradigm—manufacturing serial, standardized, identical components for use in nuclear power plants can allow the SMR industry to use the learning curves to predict and optimize deployment costs. Thus, SMR deployment cost estimates can be modeled using learning curve theory to provide some insight into how and when SMRs would be competitive with both the GW-class reactors and other mutual competitors. However, assuming static learning curve behavior for all aspects of SMR construction is likely an invalid approach—not all components and systems in SMRs will be subject to learning, and those that are subject to learning may not learn at the same rate. A learning curvebased model must be capable of tracking these unique behaviors. At the same time, the behavior of the aggregated and integrated SMR deployment is a more useful metric for discussion and comparison—ultimately, the most useful learning curve information is that which describes power plant deployment as a whole. Therefore, the goal of SMR component and systems learning modeling includes a method to produce an overall power plant learning model. This report describes the mathematics of learning curves that can be used for estimating unit cost in future production for individual components and aggregated systems. All necessary assumptions are provided to support the derivations presented. Future work will demonstrate the implementation of this methodology and provide example calculations of SMR cost

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Conditioned reflex activity of rats at later periods after the end of flight aboard the Kosmos-605 biosatellite

The aftereffects of spaceflight on the higher nervous activity of rats were studied. A five lane maze with a feeding terminal was used to check such factors as transfer of experience, the habit and speed of reaching the goal in the maze, long term memory, and the dynamics of errors. During the 3rd-7th postflight week, functional disturbances in the rat HNA were manifested in the deterioration of the capacity for the transfer of experience and for locating the feeding compartment in the maze, thus indicating a general decrease of work capacity. The increased number of errors and failures pointed to exhaustion of higher nervous processes and to the weakened functional activity of the brain.

Livshits, N. N.↗

Effect of dissociation on thermodynamic properties of pure diatomic gases

A graphical method is described by which the enthalpy, entropy, and compressibility factor for the equilibrium mixture of atoms and diatomic molecules for pure gaseous elements may be obtained and shown for any dissociating element for which the necessary data exist. Results are given for hydrogen, oxygen, and nitrogen. The effect of dissociation on the heat capacity is discussed briefly.

Woolley, Harold W↗

Extremum-seeking control for an Ultrasonic/Sonic Driller/Corer (USDC) driven at high-power

Future NASA exploration missions will increasingly require sampling, in-situ analysis and possibly the return of material to Earth for further tests. One of the challenges to addressing this need is the ability to drill using for low axial loading while operating from light weight platforms (e.g., lander, rover, etc.) as well as operate at planets with low gravity. For this purpose, the authors developed the Ultrasonic/Sonic Driller/Corer (USDC) jointly with Cybersonics Inc. Studies of the operation of the USDC at high power have shown there is a critical need to self-tune to maintain the operation of the piezoelectric actuator at resonance. Performing such tuning is encountered with difficulties and to address them an extremum-seeking control algorithm is being investigated. This algorithm is designed to tune the driving frequency of a time-varying resonating actuator subjected to both random and high-power impulsive noise disturbances. Using this algorithm the performance of the actuator is monitored on a time-scale that is compatible with its slowly time-varying physical characteristics. The algorithm includes a parameter estimator, which estimates the coefficients of a function that characterizes the quality factor of the USDC. Since the parameter estimator converges sufficiently faster than the time-varying drift of the USDC's physical parameters, the proposed extremum-seeking estimation and control algorithm is potentially applicable for use as a closed-loop health monitoring system. Specifically, this system may be programmed to automatically adjust the duty-cycle of the sinusoidal driver signal to guarantee that the quality factor of the USDC does not fall below a user-defined set-point. Such fault-tolerant functionality is especially important in automated drilling applications where it is essential not to inadvertently drive the piezoelectric ceramic crystals of the USDC beyond their capacities. The details of the algorithm and experimental results will be described and discussed in this paper.

Peek-seeking estimation and control↗

Bloom Modeling and Prediction of the Harmful Algae Alexandrium in Bellingham Bay, WA

Bellingham, Washington is located near the American-Canadian border in the northwestern part of Washington state, and is bordered on its west side by the Lummi reservation. Between Lummi and Bellingham lies Bellingham bay, which has a history of harmful algae related closures dating back to 1978. The subject of this work is a genus of dinoflagellates: Alexandrium, within which many species have the capacity to produce a suite of toxins known as saxitoxin. These toxins bioaccumulate in bivalves, which in turn cause paralytic shellfish poisoning in marine consumers (mammals, birds, and fish), including humans. Symptoms in humans can range from tingling and numbness to difficulty or inability to breathe, resulting in death. Because of the longstanding history of shellfish gathering among Salish tribes and the fact that Washington is the leading U.S. producer of farmed bivalves, harmful algae blooms impact both native and non-native peoples living in the Salish Sea area negatively. The objective of this work is to identify factors which influence Alexandrium blooms in Bellingham Bay, as well as predict Alexandrium blooms in the future. The method of doing so involves two processes: an initial statistical modeling phase to find in situ and remote sensing observations correlated to bloom density (including, but not limited to: water temperature, chlorophyll-a, salinity, color dissolved organic matter, and discharge rate of local rivers), followed by use of that data as a training set for a recursive neural network. This predictive capacity may inform future closures, help ensure the safety of shellfish consumers, and act as a baseline for future modeling efforts in the region.

Harmful↗

Integrated Commercial Carbon Capture and Storage (CCS) Prefeasibility Study at Rock Springs Uplift, Wyoming (Final Report)

To establish the potential of safe, long-term commercial-scale carbon capture & storage (CCS) in southwestern Wyoming, the University of Wyoming formed a CCS coordination team (CCT) to complete a Phase I CarbonSAFE pre-feasibility study adjacent to the region’s largest coal-fired power plant, the Jim Bridger Plant (JBP). The study’s primary objective was to evaluate the potential of storing 50+ million metric tons of anthropogenic carbon dioxide (CO 2 ) in stacked reservoirs over a period of 25 years. In addition, this integrated study evaluated related aspects of carbon capture utilization & storage (CCUS) at the study site, including: (1) the CO 2 character of post-combustion flue gas from JBP and the technical capacity for retrofitting proven commercial-scale CO 2 capture technology relative to CO 2 source character and technological constraints; (2) utilization of the existing CO 2 pipeline network in the immediate vicinity of JBP for enhanced oil recovery (CO 2 -EOR) and utilizing that network as part of a regional hub for CO 2 storage from other anthropogenic sources; (3) assessment of the challenges and benefits of meeting all of CarbonSAFE programmatic Phase I goals relative to Wyoming’s carbon management regulatory framework; and (4) assessment of the community and environmental factors that may impact CCS at JBP. With respect to storage, we analyzed the potential of stacked Mesozoic reservoirs at the study site, focusing on the Entrada and Nugget sandstones. The reservoir response to injection simulations varied greatly between formations, though they both were capable of CO 2 storage. The Entrada Sandstone is relative thin (~40’) and heterogeneous; storage using one injection and production well was limited to 1.2 Mt over 25 years at the study site. The Nugget Sandstone is much thicker (> 400’) and generally homogeneous; storage using one injection and production well approached 15.0 Mt over 25 years; this scenario suggests that the storage potential in the Nugget Sandstone is close to the estimated P90 calculation of 9.6 Mt/mi 2 as models indicate a storage potential of 8.3 Mt/mi 2 at saturation. Both reservoirs’ storage capacity benefited greatly from coupling an injection well with an offset production well; total storage capacity increased and reservoir pressure stayed below critical thresholds. This indicates that implementing a pressure management strategy at the study site would optimize storage and decrease risk. Seals associated with the targeted reservoirs were shown to be capable of retaining the potential storage volumes, and the site benefits from multiple seal redundancies (i.e. > 7,000’ of seal formations). Furthermore, assessment of different reservoir variables (e.g., fluid composition, pressure, etc.) indicates all reservoirs at the study site are isolated. Storage assessments from Mesozoic reservoirs were coupled with simulations from the site’s Paleozoic reservoirs (the Weber Sandstone and Madison Limestone), which were the focus of previous study. The fully integrated stacked reservoir pre-feasibility studies suggest that the Nugget and Madison formations alone could safely store 50 million metric tons of CO 2 within the study site. Furthermore, both formations are true saline reservoirs near JBP, making them ideal target reservoirs for CO 2 sequestration. Analysis of Wyoming’s laws and regulations confirm that the State has a favorable policy environment for CCS/CCUS. The project’s economic models estimated that the following revenues collectively are sufficient to finance the project over its lifespan if CO 2 utilization is coupled with CCS via the following strategies: (1) sales of CO 2 for EOR (approximately $69 million/year); (2) use of CO 2 tax credits such as amended §45Q and §48A (approximately $484 million total); and (3) sales of low-carbon electricity and marketable carbon offset/credits into carbon-constrained markets (approximately $11-$17 million/year) to West Coast consumers. These revenue estimates are broadly consistent with other studies that concluded arbitrage in JBP retail electricity sales between California and Wyoming could help to support the cost of deploying CCS at JBP. The models also indicate that maintaining a successful business case for long-term CCS -- wherein associated capture, transportation and operational costs are fully addressed at JBP -- is reliant on numerous external factors that complicate predictions. This study suggests that this site meets the CarbonSAFE program’s requirements of being able to feasibly store 50+ million metric tons of CO 2 over 25 years within the site’s stacked reservoirs, especially if coupled with pressure management strategies. This study suggests that the Nugget Sandstone and the Madison Limestone are two of the best reservoirs in the State with respect to overall storage capacity. In addition, the site’s proximity to existing CO 2 transportation networks, CO 2 -EOR opportunities, ability to sell to markets that value low-carbon electricity, Wyoming’s existing carbon regulatory framework, and a public that is well-educated with respect to energy markets and issues collectively increase the potential for implementing commercial-scale CCS adjacent to the JBP. With respect to the available technical and non-technical site data, and the reservoir quality at the study site, we suggest that this site is capable of moving directly into Phase III of the CarbonSAFE program.

01 COAL, LIGNITE, AND PEAT↗

Chemical factors controlling the behaviour of oxide cathodes in batteries

Oxide cathodes enable high-energy lithium-ion and sodium-ion batteries, with their performances fundamentally governed by three interrelated chemical factors: electronic configuration, chemical bonding, and chemical reactivity. Here, we illustrate how these factors dictate the redox energy, structural stability, ionic and electronic transport, and interfacial behavior in both layered oxide and polyanion oxide cathodes. We discuss how crystal-field effects and octahedral-site stabilization energies influence cation migration, and how inductive effects tune bond covalency and operating voltages. We also explain how chemical bonding governs thermal stability, gas evolution, and first-cycle capacity loss, and how alignment of transition-metal redox band with the oxygen 2p band determines electrolyte reactivity. Comparison between lithium and sodium layered oxides further reveals how differences in Li-O and Na-O bond ionicity affect chemical reactivity. Finally, we outline strategies including compositional tuning, surface doping, and electrolyte optimization, and emphasize how high-throughput, data-driven approaches in guiding the design of next-generation oxide cathodes.

25 ENERGY STORAGE↗

Contrasting behaviour under pressure reveals the reasons for pyramidalization in tris(amido)uranium(III) and tris(arylthiolate) uranium(III) molecules

A range of reasons has been suggested for why many low-coordinate complexes across the periodic table exhibit a geometry that is bent, rather a higher symmetry that would best separate the ligands. The dominating reason or reasons are still debated. Here we show that two pyramidal UX3 molecules, in which X is a bulky anionic ligand, show opposite behaviour upon pressurisation in the solid state. UN" 3 (UN3, N" = N(SiMe 3 ) 2 ) increases in pyramidalization between ambient pressure and 4.08 GPa, while U(SAr) 3 (US3, SAr = S-C 6 H 2 - t Bu 3 –2,4,6) undergoes pressure-induced planarization. This capacity for planarization enables the use of X-ray structural and computational analyses to explore the four hypotheses normally put forward for this pyramidalization. The pyramidality of UN3, which increases with pressure, is favoured by increased dipole and reduction in molecular volume, the two factors outweighing the slight increase in metal-ligand agostic interactions that would be formed if it was planar. The ambient pressure pyramidal geometry of US3 is favoured by the induced dipole moment and agostic bond formation but these are weaker drivers than in UN3; the pressure-induced planarization of US3 is promoted by the lower molecular volume of US3 when it is planar compared to when it is pyramidal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Empowering multicomponent cathode materials for sodium ion batteries by exploring three-dimensional compositional heterogeneities

Affordable sodium ion batteries hold great promise for revolutionizing stationary energy storage technologies. Sodium layered cathode materials are usually multicomponent transition metal (TM) oxides and each TM plays a unique role in the operating cathode chemistry, e.g., redox activity, structural stabilization. Engineering the three-dimensional (3D) distribution of TM cations in individual cathode particles can take advantage of a depth-dependent charging mechanism and enable a path towards tuning local TM–O chemical environments and building resilience against cathode–electrolyte interfacial reactions that are responsible for capacity fading, voltage decay and safety hazards. In this study, we create 3D compositional heterogeneity in a ternary and biphasic (O3–P3) sodium layered cathode material (Na 0.9 Cu 0.2 Fe 0.28 Mn 0.52 O 2 ). The cells containing this material deliver stable voltage profiles, and discharge capacities of 125 mA h g –1 at C/10 with almost no capacity fading after 100 cycles and 75 mA h g –1 at 1C with negligible capacity fading after 200 cycles. The direct performance comparison shows that this material outperforms other materials with similar global compositions but different mesoscale chemical distributions. Synchrotron X-ray spectroscopy/imaging and density functional theory studies reveal depth-dependent chemical environments due to changes to factors such as charge compensation and strength of orbital hybridization. Finally, 3D spectroscopic tomography illuminates the path towards optimizing multicomponent sodium layered cathode materials, to prevent the migration of TMs upon prolonged cycling. Furthermore, the study reports an inaugural effort of multifaceted and counterintuitive investigation of sodium layered cathode materials and strongly implies that there is plenty of room at the bottom by tuning nano/meso scale chemical distributions for stable cathode chemistry.

25 ENERGY STORAGE↗

Ecological generalism drives hyperdiversity of secondary metabolite gene clusters in xylarialean endophytes

Although secondary metabolites are typically associated with competitive or pathogenic interactions, the high bioactivity of endophytic fungi in the Xylariales, coupled with their abundance and broad host ranges spanning all lineages of land plants and lichens, suggests that enhanced secondary metabolism might facilitate symbioses with phylogenetically diverse hosts. Here, we examined secondary metabolite gene clusters (SMGCs) across 96 Xylariales genomes in two clades (Xylariaceae s.l. and Hypoxylaceae), including 88 newly sequenced genomes of endophytes and closely related saprotrophs and pathogens. We paired genomic data with extensive metadata on endophyte hosts and substrates, enabling us to examine genomic factors related to the breadth of symbiotic interactions and ecological roles. All genomes contain hyperabundant SMGCs; however, Xylariaceae have increased numbers of gene duplications, horizontal gene transfers (HGTs) and SMGCs. Enhanced metabolic diversity of endophytes is associated with a greater diversity of hosts and increased capacity for lignocellulose decomposition. Our results suggest that, as host and substrate generalists, Xylariaceae endophytes experience greater selection to diversify SMGCs compared with more ecologically specialised Hypoxylaceae species. Altogether, our results provide new evidence that SMGCs may facilitate symbiosis with phylogenetically diverse hosts, highlighting the importance of microbial symbioses to drive fungal metabolic diversity.

59 BASIC BIOLOGICAL SCIENCES↗

Variable Speed Heat Pump Sizing Guide for Mixed-Humid Climates

The similarities and differences between different capacity units in a model family will vary depending on the manufacturer. These unit specific details are critical to choosing the VSHP capacity that will yield the highest energy savings without compromising comfort. In addition, the house construction, climate, and occupant behavior will influence the balance of the heating and cooling load on the house as well as the sensible and latent cooling demand. All of these factors need to be considered when trying to select the proper unit for the highest energy savings. Based on the simulations performed in this study, it is likely that VSHPs with an enhanced dehumidification mode can be sized up to two times the cooling load of the house without any reduction in comfort when compared to a single speed heat pump assuming a typical home and occupant behavior in the mixed-humid and cold climates.

42 ENGINEERING↗

Cooperative Transmission Expansion Planning Experiment Data and Results

GO WEST is an open-source power grid modeling framework for U.S. Western Interconnection, which allows users to tailor the model depending on their research study and science questions. It covers 28 balancing authorities (BA) and 12 states in U.S. Western Interconnection. GO WEST allows users to select different number of nodes and come up with a simplified network by utilizing 10,000 nodal topology of U.S. Western Interconnection created by Texas A&M University. Users can try and select different number of nodes, mathematical formulations (linear programming vs. mixed-integer linear programming), transmission line limit scaling factors, and hurdle rate scaling factors. GO WEST offers a unit commitment and economic dispatch (UC/ED) module to simulate grid operations on an hourly scale. In this sense, users can calibrate and validate their model versions by comparing model outputs to historical datasets. TEP is an open-source transmission capacity expansion model, built on GO WEST framework. It utilizes linear programming to optimize transmission capacity addition investment on existing lines within GO WEST framework. In this sense, TEP model only increases the thermal capacity of existing transmission lines and does not add new lines to the system, which leaves the topology preserved. TEP minimizes the total cost of the system which comprises the operational cost of satisfying electricity demand (i.e., generation cost), cost of loss of load (i.e., unserved energy), cost of power flow, and cost of new transmission capacity additions (i.e., investment cost). In order to use TEP model, users need to create scenarios with GO WEST framework. In this analysis, outputs from several models are used to create future inputs to GO WEST and TEP models, including GCAM-USA, TELL, CERF and reV. This dataset includes experiment inputs and outputs from three different transmission expansion scenarios (cooperative, intermediate, and individual) for 2019 and 2059. For 2019, a base scenario to illustrate the default (i.e., historical) power grid operations is also included. This study utilizes rcp45hotter_ssp3 scenario from a previous version of GCAM-USA simulations. Sources of the shapefiles in supplementary data are HIFLD Open and U.S. Energy Atlas. Please see the README file for a detailed description of the main and supplementary data.

Capacity Expansion Model↗

IM3 Projected U.S. Western Interconnection Grid Stress Dataset

This dataset provides projected grid stress and reliability results (including all model inputs and outputs from GO WEST and TEP) for Integrated Multisector, Multiscale Modeling (IM3) Phase 2 simulations across eight different scenarios for the U.S. Western Interconnection through 2055. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States from a set of Thermodynamic Global Warming (TGW) simulations. These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 GO WEST is an open-source power grid modeling framework for the U.S. Western Interconnection, which allows users to tailor the model depending on their research study and science questions. It covers 28 balancing authorities (BAs) and 12 states in U.S. Western Interconnection. GO WEST allows users to select different number of nodes and come up with a simplified network by utilizing 10,000 nodal topology of the U.S. Western Interconnection (ACTIVSg10k). Users can select different number of nodes, mathematical formulations (linear programming vs. mixed-integer linear programming), transmission line limit scaling factors, and hurdle rate scaling factors. GO WEST offers a unit commitment and economic dispatch (UC/ED) module to simulate grid operations on an hourly scale. In this sense, users can calibrate and validate their model versions by comparing model outputs to historical datasets. TEP is an open-source transmission capacity expansion model, built on the GO WEST framework. It utilizes linear programming to optimize transmission capacity addition investment on existing lines within the GO WEST framework. The TEP model only increases the thermal capacity of existing transmission lines and does not add new lines to the system, which leaves the topology preserved. In order to use TEP model, users need to create scenarios with the GO WEST framework. Please refer to README file for a detailed description of the dataset including individual files and references.

Capacity Expansion Model↗

Basic cryogenics and materials. Phase 1

The effects of cryogenic temperatures on the mechanical and physical properties of materials are summarized. Heat capacity and thermal conductivity are considered in the context of conservation of liquid nitrogen, thermal stability of the gas stream, and the response time for changes in operating temperature. Particular attention is given to the effects of differential expansion and failure due to thermal fatigue. Factors affecting safety are discussed, including hazards created due to the inadvertent production of liquid oxygen and the physiological effects of exposure to liquid and gaseous nitrogen, such as cold burns and asphyxiation. The preference for using f.c.c. metals at low temperatures is explained in terms of their superior toughness. The limitations on the use of ferritic steels is also considered. Nonmetallic materials are discussed, mainly in the context of their LOX compatibility and their use in the form of foams and fibers as insultants, seals, and fiber reinforced composites.

Wigley, D. A.↗

Basic cryogenics and materials

The effects of cryogenic temperatures on the mechanical and physical properties of materials are summarized. Heat capacity and thermal conductivity are considered in the context of conservation of liquid nitrogen, thermal stability of the gas stream, and the response time for changes in operating temperature. Particular attention is given to the effects of differential expansion and failure due to thermal fatigue. Factors affecting safety are discussed, including hazards created due to the inadvertent production of liquid oxygen and the physiological effects of exposure to liquid and gaseous nitrogen, such as cold burns and asphyxiation. The preference for using f.c.c. metals at low temperatures is explained in terms of their superior toughness. The limitations on the use of ferritic steels is also considered. Nonmetallic materials are discussed, mainly in the context of their LOX compatibility and their use in the form of foams and fibers as insulatants, seals, and fiber reinforced composites.

Wigley, D. A.↗

Modeling fluvial erosion on regional to continental scales

The fluvial system is a major concern in modeling landform evolution in response to tectonic deformation. Three stream bed types (bedrock, coarse-bed alluvial, and fine-bed alluvial) differ in factors controlling their occurrence and evolution and in appropriate modeling approaches. Spatial and temporal transitions among bed types occur in response to changes in sediment characteristics and tectonic deformation. Erosion in bedrock channels depends upon the ability to scour or pluck bed material; this detachment capacity is often a power function of drainage area and gradient. Exposure of bedrock in channel beds, due to rapid downcutting or resistant rock, slows the response of headwater catchments to downstream baselevel changes. Sediment routing through alluvial channels must account for supply from slope erosion, transport rates, abrasion, and sorting. In regional landform modeling, implicit rate laws must be developed for sediment production from erosion of sub-grid-scale slopes and small channels.

Howard, Alan D.↗