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All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Cone Model for Halo CMEs: Application to Space Weather Forecasting

In this study, we present an innovative analytical method to determine the angular width and propagation orientation of halo Coronal Mass Ejections (CMEs). The relation of CME actual speed with apparent speed and its components measured at different position angle has been investigated. The present work is based on the cone model proposed by Zhao et al. We have improved this model by: (1) eliminating the ambiguity via a new analytical approach, (2) using direct measurements of projection onto the plane of the sky (POS), and (3) determining the actual radial speeds from projection speeds at different position angles to clarify the uncertainty of projection speeds in previous empirical models. Our analytical approach allows us to use coronagraph data to determine accurately the geometrical features of POS projections, such as major axis, minor axis, and the displacement of the center of its projection, and to determine the angular width and orientation of a given halo CME. Our approach allows for the first time the determination of the actual CME speed, width, and source location by using coronagraph data quantitatively and consistently. The method greatly enhances the accuracy of the derived geometrical and kinematical properties of halo CMEs, and can be used to optimize Space Weather forecasts. The applied model predications are in good agreement with observations.

Xie, Hong↗
NASA NTRS2006

Studying the MLT by a Combined Analysis of SABER/TIMED and Lidar Measurements

The SABER instrument on board the TIMED Satellite is a limb scanning infrared radiometer designed to measure temperature and minor constituent vertical profiles and energetics parameters in the mesosphere and lower thermosphere (MLT). The measurements have been performed continuously since January 25, 2002 to provide excellent coverage for both hemispheres. The Leibniz-Institute of Atmospheric Physics (LAP) at Kuehlungsborn, Germany (54N, 12E) operates two lidar instruments, using three different temperature measurement methods, optimized for three altitude ranges. The total altitude range of the lidar installation lies from 1 to 105 km. Another instrument used for intercomparison is the ALOMAR RMR lidar, located at Andoya, Norway (69N, 16E). We have searched the SABER and lidar datasets for coincidental common volume measurements within plus or minus 1 degree in latitude, plus or minus 2 degrees in longitude and approx. 1 hour in time for the sake of (a) comparison of measured temperatures; (b) validation of the models used in SABER data analysis; and (c) extracting new information about MLT parameters. In this work we applied the non-LTE ALI-ARMS code designed to calculate the nonequilibrium radiance in different viewing geometries to the analysis of measurements which satisfied these search criteria. The results of this analysis (a) support the application of higher value of CO2-O quenching rate (6e-12 cubic centimeters per second) by the non-LTE temperature retrievals from the SABER 15 micrometer limb radiance data, and (b) demonstrate the importance of accounting for the vibrational-vibrational energy exchange among the CO2 isotopes for accurate temperature retrievals. Using temperature profiles obtained in lidar measurements as inputs for the retrieval algorithm we also retrieved the nighttime CO2 densities from the SABER 15 micrometer limb radiances and compared them with the model and climatology CO2 data used in the SABER nighttime temperature retrievals.

Feofilov, A. G.↗
NASA NTRS2008

Science Goals in Radiation Protection for Exploration

Space radiation presents major challenges to future missions to the Earth s moon or Mars. Health risks of concern include cancer, degenerative and performance risks to the central nervous system, heart and lens, and the acute radiation syndromes. The galactic cosmic rays (GCR) contain high energy and charge (HZE) nuclei, which have been shown to cause qualitatively distinct biological damage compared to terresterial radiation, such as X-rays or gamma-rays, causing risk estimates to be highly uncertain. The biological effects of solar particle events (SPE) are similar to terresterial radiation except for their biological dose-rate modifiers; however the onset and size of SPEs are difficult to predict. The high energies of GCR reduce the effectiveness of shielding, while SPE s can be shielded however the current gap in radiobiological knowledge hinders optimization. Methods used to project risks on Earth must be modified because of the large uncertainties in projecting health risks from space radiation, and thus impact mission requirements and costs. We describe NASA s unique approach to radiation safety that applies probabilistic risk assessments and uncertainty based criteria within the occupational health program for astronauts and to mission design. The two terrestrial criteria of a point estimate of maximum acceptable level of risk and application of the principle of As Low As Reasonably Achievable (ALARA) are supplemented by a third requirement that protects against risk projection uncertainties using the upper 95% confidence level (CL) in radiation risk projection models. Exploration science goals in radiation protection are centered on ground-based research to achieve the necessary biological knowledge, and in the development of new technologies to improve SPE monitoring and optimize shielding. Radiobiology research is centered on a ground based program investigating the radiobiology of high-energy protons and HZE nuclei at the NASA Space Radiation Laboratory (NSRL) located at DoE s Brookhaven National Laboratory in Upton, NY. We describe recent NSRL results that are closing the knowledge gap in HZE radiobiology and improving exploration risk estimates. Linking probabilistic risk assessment to research goals makes it possible to express risk management objectives in terms of quantitative metrics, which include the number of days in space without exceeding a given risk level within well defined confidence limits, and probabilistic assessments of the effectiveness of design trade spaces such as material type, mass, solar cycle, crew selection criteria, and biological countermeasures. New research in SPE alert and risk assessment, individual radiation sensitivity, and biological countermeasure development are described.

Cucinotta, Francs A.↗
DOE OSTI2022

Case Study: Hybridizing Nuclear Energy Systems in the U.S.

This case study was presented at the ICTP-IAEA VIRTUAL Course on Nuclear-Renewable Integrated Energy Systems: Phenomenology, Research and Development. It provides preliminary results on an analysis of hybridizing the two nuclear power plants owned by Xcel Energy and located in Minnesota. The analysis extends previous analyses that provided only price-taker results. Those assume adjusting the generation sold to the grid does not impact locational marginal electricity prices nor do they estimate impacts on the total net cost to serve the load. This presentation summarizes the new technique that was developed to both optimize the size and operations of the hybridized system and the resulting impacts on the grid when it is operated optimally.

ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2004

The International Global Network of Geodetic Fiducial Stations

Scientific need and technological opportunity require that we move toward implementing a global network of geodetic fiducial stations which feature co-located SLR, VLBI, GNSS, and DORIS instrumentation. Earth science of the next decade will require more accurate global change measurements of sea level topography, sea level change, polar ice mass balance, hydrological and atmospheric mass flux. and topographic deformation, real time mm scale navigation and precision time transfer on a global scale. These scientific requirements have been translated into a goal of mm scale annual stability for the terrestrial reference frame, earth orientation parameters, as well as the orbit and clock determinations tbr the GNSS systems. To meet these challenges, the four geodetic observing systems must be more tightly integrated in technology, location, and analysis. NASA strongly supports the objectives of the IGGOS initiative vis NASA's National Geodetic Observatory and INDIGO programs. The Global networks of GNSS, SLR. and VLBI observatories are for the most part poorly suited for these new demands. These important geodetic networks have evolved with little planning yet these systems are providing essential measurements to a wide swath of society. New signal structures in the GPS and the developing Galileo GNSS will soon require replacement of the GNSS receivers. The SLR network is poorly distributed globally, requires labor intensive observations and analysis, and for the most part relies upon antiquated technology. The VLBI observatories utilize large radio telescopes in remote regions that are poorly distributed globally. Co-location of these networks is sparse and co-location errors contribute significantly to the observing error spectrum. Increasing use of the S and X band by commercial and other government services will also contribute to increased observational errors. The time is upon us for an international effort to develop an optimized global geodetic fiducial network of twelve or more integrated automated geodetic observatories that will provide in near real time high density mea.surements of Earth orientation, geodetic positioning, and GNSS system monitoring. The strategic goal for the optimized global fiducial network should be efficient autonomous operation, real time data streaming to analysis centers with an integrated near real time analysis capability for all four observing systems. These goals are achievable in the next decade given the dramatic technological improvements in all geodetic systems. For VLBI, the BKG TIGO might be viewed as a preliminary prototype of technology for fundamental stations. Mark 5, PC-VSI. e-VLBI broadband development efforts are laying the groundwork to reduce the aperture of the VLBI antennas and to allow for precision mm level co-location of observing systems. Operating costs and enhanced accuracy would accrue from the elimination of hydrogen maser clocks using double differencing, GNSS time transfer technology, GHz broadband recording, real time analysis, and mm wavelength VLBI observations. A global geodetic fiducial network will not be realizable without international efforts and the support of the four services.

LaBrecque, John↗
DOE OSTI2022

A new dynamic zOnal model with air-diffuser (DOMA) - Application to thermal comfort prediction

A new Dynamic zOnal Model with Air-diffuser (DOMA) was developed. Several case studies were investigated and tested to evaluate and validate this program using measurement data. This new model was integrated into a TRaNsient SYstems Simulation program library and coupled with the multi-zone thermal model. The DOMA/TRNSYS coupled model was then used to predict room temperature distribution over an entire day of a single-zone building. The results show that increasing the heating outputs of the electric floor system, for example, from 75 to 200 W/m 2 , would not effectively improve the indoor thermal comfort, since the thermostat will reach the set point first and then turn off the system before the room gets enough heat and reach a comfortable level. This indicates the importance of selecting an appropriate location and set point for the thermostat when using a floor heating system. This potential thermal comfort issue can only be identified through the two-node model with a dynamic zonal model rather than the conventional PMV model, which thus suggests that for optimizing indoor thermal comfort of a building equipped with a time-sensitive control strategy and/or HVAC system, the TSENS results obtained from the two-node model integrated with DOMA are more appropriate than PMVs.

Construction & Building Technology↗
NASA NTRS2014

An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

NASA's space data-communications infrastructure-the Space Network and the Ground Network-provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft. The Space Network operates several orbiting geostationary platforms (the Tracking and Data Relay Satellite System (TDRSS)), each with its own servicedelivery antennas onboard. The Ground Network operates service-delivery antennas at ground stations located around the world. Together, these networks enable data transfer between user spacecraft and their mission control centers on Earth. Scheduling data-communications events for spacecraft that use the NASA communications infrastructure-the relay satellites and the ground stations-can be accomplished today with software having an operational heritage dating from the 1980s or earlier. An implementation of the scheduling methods and algorithms disclosed and formally specified herein will produce globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary algorithms, a class of probabilistic strategies for searching large solution spaces, is the essential technology invoked and exploited in this disclosure. Also disclosed are secondary methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithms themselves. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure within the expected range of future users and space- or ground-based service-delivery assets. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally. The generalized methods and algorithms are applicable to a very broad class of combinatorial-optimization problems that encompasses, among many others, the problem of generating optimal space-data communications schedules.

ground stations↗
DOE OSTI2021

AC Power Flow Based DLMP Calculation and Decomposition Method to Smooth Power Fluctuation of Distributed Renewable Energy Sources

As the penetration of renewable energy sources increases, the growing renewable power variability brings ramping issues to power systems. Meanwhile, the development of distributed energy resources (DERs) makes the distribution systems to provide both energy and ancillary services. To incentivise individual resources and customers to alleviate ramping issues on the demand side, a two-stage distribution locational marginal price (DLMP) calculation and decomposition method is developed to formulate the marginal power ramping price for DERs. In the first stage of the proposed method, a distribution system operator market scheduling model based on AC optimal power flow is designed to estimate the optimal operating point of the distribution system. Subsequently, the voltage and power flow constraints are linearised in stage two to calculate DLMP. Finally, based on the Lagrange function and sensitivity factors, DLMP is decomposed to the marginal costs for active/reactive power, voltage management, power loss and power variability. Case studies demonstrate that the proposed model can effectively smooth the power fluctuation and reduce the ramping flexibility requirements of distribution systems.

AC optimal power flow↗
NASA NTRS1979

Telecommunications network optimization

Analysis discusses STACOM (state criminal justic communication) network topology program used to design and evaluate digital telecommunications networks STACOM employs ESAU-WILLIAMS technique to search for direct links between system terminations and regional switching center. Inputs include traffic data, terminal locations, and functional requirements.

Lee, J.↗
DOE OSTI2023

Optimal Sizing of Movable Energy Resources for Enhanced Resilience in Distribution Systems: A Techno-Economic Analysis

This article introduces a techno-economic analysis aimed at identifying the optimal total size of movable energy resources (MERs) to enhance the resilience of electric power supply. The core focus of this approach is to determine the total size of MERs required within the distribution network to expedite restoration after extreme events. Leveraging distribution line fragility curves, the proposed methodology generates numerous line outage scenarios, with scenario reduction techniques employed to minimize computational burden. For each reduced multiple line outage scenario, a systematic reconfiguration of the distribution network, represented as a graph, is executed using tie-switches within the system. To evaluate each locational combination of MERs for a specific number of these resources, the expected load curtailment (ELC) is calculated by summing the load curtailment within microgrids formed due to multiple line outages. This process is repeated for all possible locational combinations of MERs to determine minimal ELC for each MER total size. For every MER total size, the minimal ELCs are determined. Finally, a techno-economic analysis is performed using power outage cost and investment cost of MERs to pinpoint an optimal total size of MERs for the distribution system. To demonstrate the effectiveness of the proposed approach, case studies are conducted on the 33-node and the modified IEEE 123-node distribution test systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Model-Based Framework to Optimize Charger Station Deployment for Battery Electric Vehicles

The development of battery electric vehicles (BEVs) is accelerating due to their environmental advantages over gasoline and diesel-powered vehicles, including a decrease in air pollution and an increase in energy efficiency. The deployment of charging infrastructure will need to increase to keep pace with demand, especially for large commercial vehicles for which few public chargers currently exist. In this paper, a new flexible framework is proposed for optimizing the placement of charging stations for BEVs, within which different physical models and optimization techniques may be used. Furthermore, a set of metrics is suggested to help enforce complex constraints and facilitate direct comparison between different optimization techniques. Unlike many existing charger placement techniques, the proposed method directly considers the historical driving patterns on a vehicle-by-vehicle basis, using transparent models to assess impacts of candidate charger placements, thus improving the explainability of the results. In the developed framework, modeled BEVs are first generated along the road network to mimic historical traffic data and are simulated traveling along a given route according to a simplified vehicle model. During the simulation, the charger placement problem is initially relaxed to allow vehicles to charge at any node along the road network, and vehicle states are tracked to assess areas of high charging demand. Charging stations are then placed based on the results of the relaxed simulation, and suggested placements are evaluated via road network simulation with fixed charger locations. This proposed framework is applied to a sample problem of placing charging stations along five major highway corridors for Class 8 over-the-road electric trucks. A novel mixed integer programming (MIP) formulation is proposed to optimize charger placements based upon the expected charging demand. Constraints were imposed on the final placement results to limit expected wait times at each station and ensure a minimum threshold of trucking routes are viable for BEVs. The results demonstrate the flexibility and potential effectiveness of the developed model-based framework for scalable charger station deployment.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Performance of an Isobaric Hybrid Compressed Air Energy Storage System at Minimum Entropy Generation

Efficient, large-scale, and cost-effective energy storage systems provide a means of managing the inherent intermittency of renewable energy sources and drastically increasing their utilization. Compressed air energy storage (CAES) and its derivative architectures have received much attention as a viable solution; however, optimization objectives for these systems have not been thoroughly investigated in the literature. In this work, a hybrid thermal and compressed air energy storage (HT-CAES) system is investigated that mitigates the shortcomings of the otherwise attractive conventional CAES systems and its derivatives—shortcomings such as strict geological locations, low energy densities, and the production of greenhouse gas emissions. The HT-CAES system allows a portion of the available energy to operate a compressor and the remainder to be converted and stored in the form of heat through joule/resistive heating in a high-temperature, sensible, thermal energy storage medium. Internally reversible and irreversible HT-CAES system assumptions were investigated, in addition to regenerative and non-regenerative design configurations. Several system optimization criteria were examined—including maximum energy efficiency, maximum exergy efficiency, maximum work output, and minimum entropy generation—with a focus on whether the latter may lead to conclusive design guidelines in a real system. It is shown that an HT-CAES system designed based on a minimum entropy generation objective may operate at a lower energy and exergy efficiency as well as lower output power than otherwise achievable. Furthermore, optimization objective equivalence is shown to be limited to certain design conditions.

25 ENERGY STORAGE↗
DOE OSTI2022

Experimentally informed structure optimization of amorphous TiO 2 films grown by atomic layer deposition

Amorphous titanium dioxide TiO 2 (a-TiO 2 ) has been widely studied, particularly as a protective coating layer on semiconductors to prevent corrosion and promote electron–hole conduction in photoelectrochemical reactions. The stability and longevity of a-TiO 2 is strongly affected by the thickness and structural heterogeneity, implying that understanding the structure properties of a-TiO 2 is crucial for improving the performance. This study characterized the structural and electronic properties of a-TiO 2 thin films (~17 nm) grown on Si by atomic layer deposition (ALD). Fluctuation spectra V(k) and angular correlation functions were determined with 4-dimensional scanning transmission electron microscopy (4D-STEM), which revealed the distinctive medium-range ordering in the a-TiO 2 film. A realistic atomic model of a-TiO 2 was established guided by the medium-range ordering and the previously reported short-range ordering of a-TiO 2 film, as well as the interatomic potential. The structure was optimized by the StructOpt code using a genetic algorithm that simultaneously minimizes energy and maximizes the match to experimental short- and medium-range ordering. The StructOpt a-TiO 2 model presents improved agreements with the medium-range ordering and the k-space location of the dominant 2-fold angular correlations compared with a traditional melt-quenched model. The electronic structure of the StructOpt a-TiO 2 model was studied by ab initio calculations and compared to the crystalline phases and experimental results. Finally, this work uncovered the medium-range ordering in a-TiO 2 thin films and provided a realistic a-TiO 2 structure model for further investigation of structure–property relationships and materials design. In addition, the improved multi-objective optimization package StructOpt was provided for structure determination of complex materials guided by experiments and simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Dopant Optimization of Donors in Semiconductor Opening Switches to Eliminate Prepulse

Semiconductor opening switches are solid-state devices capable of delivering nanosecond, hundreds of kilovolts pulses by interrupting kiloamps of current. The interruption of the current occurs in a moderately doped p-region when a high electric field region (HFR) is formed. The HFR occurs because the reverse pumping current cannot be supported by the saturation velocity and majority carrier concentration of the doping level. However, the donor profile also significantly affects the pulse performance. A secondary prepulse occurs if a secondary HFR is formed at the interface of the background n-doping and N+ doping (X n ) . By moving the location of X n deeper into the diode, the effect of the prepulse is reduced. This article investigates the effect of the donor doping profile on the performance metrics of semiconductor opening switches through technology computer-aided design (TCAD) simulations and experimental results. Through a SILVACO TCAD optimization, we designed a P + /p/n - base/n/N + where the intersection of the moderate p-region and intrinsic n-base region (X p ) is at 160 μm and X n is at 220 μm. This profile is fabricated via silicon epitaxy. Experimentally, it is shown that a deep X n (220 μm) compared with a shallow X n (300 μm) reduces the rise time by >5× . In addition, the magnitude of current density during interruption affects the prepulse foot and pulse shape. At lower current densities without the graded donor profile, high peak voltages are not achieved. Comparing the experimental results to the TCAD simulations shows that the model is predictive under high-current densities in the semiconductor opening switch (SOS) regime.

nanosecond pulse power↗
DOE OSTI2026

Public water supply infrastructure extensification and diversification in surface waters is insufficient to meet future demands in Texas

The data were developed to evaluate the capacity of existing and potential new surface water supply infrastructure to meet projected public water demands across districts in Texas under multiple future socioeconomic and climate scenarios. The database integrates hydrologic, water quality, infrastructure, energy, cost, demographic, and demand-projection information for candidate surface water supply locations. Candidate sites include stream reaches, waterbodies, reservoir surplus locations, and potential new reservoir sites. Water availability is characterized using historical and projected flow conditions, while site suitability is evaluated using five indicators: Water Availability Index (WAI), Water Quality Index (WQI), Energy Requirement Index (ERI), Water Treatment Cost (WTC), and Water Infrastructure Cost (WIC). The datasets include statewide candidate-site information, district-level demand projections under Shared Socioeconomic Pathways (SSPs), runoff-based allocation constraints, climate-stress metrics, and optimization outputs evaluating alternative infrastructure planning strategies. Optimization results compare Business-as-Usual (BAU) and All Surface Water (AllSW) demand-management approaches under both scaled and fixed cost-cap strategies. Associated validation datasets provide district-level feasibility assessments, infrastructure selection outcomes, cost-cap utilization, demand satisfaction metrics, and constraint diagnostics. Additional datasets quantify projected changes in storage and flow conditions as well as water availability stress for both existing and newly selected intake locations under the SSP5 scenario for mid-century and late-century climate conditions. Together, these datasets support assessment of the extent to which surface-water infrastructure expansion and diversification strategies can satisfy future public water demands while accounting for hydrologic, economic, and planning constraints across Texas. Dataset(s) Description Dataset_preoptimization.xlsx Comprehensive pre-optimization dataset containing candidate water-supply sites and associated hydrologic, water-quality, infrastructure, climate, demographic, runoff, and demand-projection variables used as inputs to the optimization analyses. Includes variable descriptions and the full statewide candidate-site database. District_level_site_selection.zip - Compressed archive containing all SSP-specific district-level optimization result files MESIO_ssp1_results.xlsx District-level site selection results for SSP1 (MESIO). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. MESID_ssp2_results.xlsx District-level site selection results for SSP2 (MESID). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. LCMRD_ssp3_results.xlsx District-level site selection results for SSP3 (LCMRD). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. IRDev-Low_ssp4l_results.xlsx District-level site selection results for SSP4-Low (IRDev-Low). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. IRDev-High_ssp4h_results.xlsx District-level site selection results for SSP4-High (IRDev-High). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. RSIM_ssp5_results.xlsx District-level site selection results for SSP5 (RSIM). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. tx_hydrological_stress.xlsx Hydrological stress dataset for existing and newly selected intake locations. Includes projected mid-century and late-century changes, gain/loss classifications, planning strategy information, and accompanying variable descriptions. Also includes water-stress metrics derived from historical and projected low-flow conditions.

Okoye, Perpetua I. (ORCID:0000000215545033)↗
DOE OSTI2020

Gaining Perspective on Unconventional Well Design Choices through Play-level Application of Machine Learning Modeling

The recent development of unconventional oil and gas (O&G) reservoirs has led to an abundant hydrocarbon supply, both domestically and globally. However, there is a continued push to develop new and innovative approaches to improve exploration and extraction efficiencies and overall well productivity moving forward. Substantial improvements in unconventional O&G development are expected through optimized well completion and stimulation strategies aimed at maximizing well productivity. Optimizing well designs will require tailoring to the distinctive geologic conditions present for any newly placed well. To better evaluate the impact of well design attributes and their associated interactions on productivity in a major unconventional play, multivariate machine learning-based models that use empirical datasets were developed. A gradient boosted regression tree (GBRT) algorithm was applied. GBRT has been narrowly investigated for O&G applications but enables straightforward parametric importance and influence evaluation, as well as assessment of parameter interaction effects. Models were trained on well design and locational parameters that serve as a proxy for variable geologic conditions to estimate two types of productivity indicator response variables strongly correlated to estimated ultimate recovery (EUR). The dataset utilized consists of over 7,000 well observations that cover the majority of the productive region of the Marcellus Shale. Model performance was evaluated and algorithm parameters tuned by analyzing the goodness-of-fit for simulated results against observed data in a cross-validation approach. Models were found capable of 73–79 percent prediction accuracy on held out testing data of gas equivalent production and can be used to inform future well design and placement decisions for increasing EUR per well and improving overall field-level recovery. Study results indicate that Marcellus well performance improves most with upscaling perforated interval lengths and water and proppant volumes per foot; but relative productivity improvements are spatially dependent across the play. Finally, optimal combinations of water and proppant on well performance were found to vary depending on well location, emphasizing the utility of data-driven models capable of broad application across a play of interest for informing tailored well design approaches prior to their field deployment.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2021

MTW-OPAL: a technology development platform for ultra-intense optical parametric chirped-pulse amplification systems

Optical parametric chirped-pulse amplification implemented using multikilojoule Nd:glass pump lasers is a promising approach for producing ultra-intense pulses (>10 23 W/cm 2 ). We report on the MTW-OPAL Laser System, an optical parametric amplifier line (OPAL) pumped by the Nd:doped portion of the multi-terawatt (MTW) laser. This midscale prototype was designed to produce 0.5-PW pulses with technologies scalable to tens of petawatts. Technology choices made for MTW-OPAL were guided by the longer-term goal of two full-scale OPALs pumped by the OMEGA EP to produce 2 × 25-PW beams that would be co-located with kilojoule–nanosecond ultraviolet beams. Several MTW-OPAL campaigns that have been completed since “first light” in March 2020 show that the laser design is fundamentally sound, and optimization continues as we prepare for “first-focus” campaigns later this year.

42 ENGINEERING↗
DOE OSTI2019

Optimal Iterative Method for Network Utility Maximization with Intertemporal Constraints

Network utility maximization (NUM) has been widely used to solve the optimal resource allocation problem in wireless network and power systems. The network planner aims to allocate generation and demand over producers and consumers such that social welfare is maximized while supply and demand are balanced, and network constraints such as branch capacity constraints are satisfied. However, when taking into account dynamics of agents, such as ramp rate constraints on power output for suppliers and impact of cumulative prior consumption on current demand for consumers, a single-period formulation is not sufficient. We propose an iterative method for the multi-period NUM with intertemporal constraints based on dual decomposition. It features a price iteration scheme that achieves optimal social welfare, and the algorithm is guaranteed to converge if proper concavity condition holds. We illustrate the iterative algorithm by power system examples. It is shown that similar to locational marginal price (LMP) in power systems, time-varying congestion prices arise when there exists binding branch constraints. Simulation results also demonstrate that there is increase in social welfare compared to a single-period formulation.

Ma, Ke↗