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At least 1,243 records · Page 69

Economic evaluation of the Hepatitis C virus elimination program in the country of Georgia, 2015 to 2017

Abstract Background and Aims In 2015, the country of Georgia launched an elimination program aiming to reduce the prevalence of Hepatitis C virus (HCV) infection by 90% from 5.4% prevalence (~150 000 people). During the first 2.5 years of the program, 770 832 people were screened, 48 575 were diagnosed with active HCV infection, and 41 483 patients were treated with direct‐acting antiviral (DAA)‐based regimens, with a >95% cure rate. Methods We modelled the incremental cost‐effectiveness ratio (ICER) of HCV screening, diagnosis and treatment between April 2015 and November 2017 compared to no treatment, in terms of cost per quality‐adjusted life year (QALY) gained in 2017 US dollars, with a 3% discount rate over 25 years. We compared the ICER to willingness‐to‐pay (WTP) thresholds of US$4357 (GDP) and US$871 (opportunity cost) per QALY gained. Results The average cost of screening, HCV viremia testing, and treatment per patient treated was $386 to the provider, $225 to the patient and $1042 for generic DAAs. At 3% discount, 0.57 QALYs were gained per patient treated. The ICER from the perspective of the provider including generic DAAs was $2285 per QALY gained, which is cost‐effective at the $4357 WTP threshold, while if patient costs are included, it is just above the threshold at $4398/QALY. All other scenarios examined in sensitivity analyses remain cost‐effective except for assuming a shorter time horizon to the end of 2025 or including the list price DAA cost. Reducing or excluding DAA costs reduced the ICER below the opportunity‐cost WTP threshold. Conclusions The Georgian HCV elimination program provides valuable evidence that national programs for scaling up HCV screening and treatment for achieving HCV elimination can be cost‐effective.

Tskhomelidze, Irina↗

Online peak-aware energy scheduling with untrusted advice

This paper studies the online energy scheduling problem in a hybrid model where the cost of energy is proportional to both the volume and peak usage, and where energy can be either locally generated or drawn from the grid. Inspired by recent advances in online algorithms with Machine Learned (ML) advice, we develop parameterized deterministic and randomized algorithms for this problem such that the level of reliance on the advice can be adjusted by a trust parameter. We then analyze the performance of the proposed algorithms using two performance metrics: robustness that measures the competitive ratio as a function of the trust parameter when the advice is inaccurate, and consistency for competitive ratio when the advice is accurate. Since the competitive ratio is analyzed in two different regimes, we further investigate the Pareto optimality of the proposed algorithms. Our results show that the proposed deterministic algorithm is Pareto-optimal, in the sense that no other online deterministic algorithms can dominate the robustness and consistency of our algorithm. Furthermore, we show that the proposed randomized algorithm dominates the Pareto-optimal deterministic algorithm. Our large-scale empirical evaluations using real traces of energy demand, energy prices, and renewable energy generations highlight that the proposed algorithms outperform worst-case optimized algorithms and fully data-driven algorithms.

Lee, Russell↗

Modular Adaptive Packing for Integrally Cooled Absorbers

Process intensification is one cornerstone in ION Clean Energy’s (ION) efforts to lowering CO2 capture cost. ION has modeled, designed, and fabricated an innovative gas-liquid contactor known as Modular Adaptive Packing (MAP). During two successful SBIR Phase I and II projects entitled: “Rapid Design and Testing of Novel Gas-Liquid Contacting Devices for Post-Combustion CO2 Capture via 3D-printing”, ION developed and proved this new technology at bench scale. MAP, a 3D-printed lattice-structured packing, combines the absorber gas/liquid contactor with an innovative in-situ heat-exchanger. Thanks to the capabilities of 3D-printing, the lattice structure of MAP contains hollow channels through which coolant water can be pumped to remove the heat of reaction from CO2 absorption. ION refers to this novel method of heat exchange as intracooling. After 25.4 cm (10 in) diameter MAP modules were fabricated, ION built and tested a packing characterization rig at its pilot facility in Boulder, Colorado, U.S.A. To provide baseline results for the characterization rig, ION tested Sulzer’s Mellapak™ 250Y (MP250Y) as a standard structured packing. ION’s MAP was then compared directly to the baseline MP250Y packing to evaluate key indicators including pressure drop, liquid hold-up, and effective area. MAP has a higher pressure drop than MP250Y at the same gas velocities in addition to greater liquid holdup. However, ION found that MAP displays a higher wetting coverage of 93% compared to 65% for MP250Y and reduces shearing forces that result in undesirable droplet formation. Using Optimized Gas Treating’s (OGT) rate-based simulation software ProTreat®, a conceptual evaluation of MAP was modeled for a CO2 absorber using 30 wt% MEA solvent over a range of lean loadings at 90% CO2 capture from a coal-fired power plant. ION modeled a 25-meter column absorber for both the standard MP250Y packing and a hybrid column. The hybrid absorber contained 10 m of MP250Y packing at the top and bottom with the middle 5 meters comprised of MAP. Compared to a traditional intercooled absorber, MAP can remove 22% more heat and increase overall MEA carrying capacity by 4% without increasing overall pressure drop.

20 FOSSIL-FUELED POWER PLANTS↗

International Collaboration Activities in Geologic Disposal Research: FY2021 Progress

This report describes the FY21 status of international collaboration regarding geologic disposal research in the Spent Fuel and Waste Disposition (SFWD) Campaign. Since 2012, in an effort coordinated by Lawrence Berkeley National Laboratory, SFWD has advanced active collaboration with several international geologic disposal programs across the world. Such collaboration has allowed the SFWD Campaign to benefit from a deep knowledge base in regards to alternative repository environments developed over decades and has provided a framework for active peer-to-peer research participation in international groups which conduct, analyze, and model performance-relevant processes. Via international collaboration, the SFWD Campaign also benefits from substantial international investments in research facilities (such as underground research laboratory testing and modeling) and achieves cost savings via joint funding of expensive field experiments. To date, SFWD’s International Disposal R&D Program has established formal collaboration agreements with multiple international initiatives and various international partners, and national lab scientists associated with SFWD have conducted a large number of specific collaborative R&D activities that align well with its R&D priorities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Distribution Grid Impacts of Community Solar [Slides]

Community solar (CS) projects often face uncertain interconnection costs and fees associated with distribution grid infrastructure upgrades required to connect the project. These costs can determine the economic viability of a CS project, but they are difficult to assess. Cost uncertainty can discourage new projects and prevent communities from accessing the benefits of community solar projects. At the same time, CS deployment strategies hold potential to defer or avoid some distribution costs due to new loads. To mitigate CS interconnection costs, it is important to find least-cost combinations of distribution system infrastructure solutions (transformer upgrades, reconductoring, voltage regulators, storage), and to understand how location of CS projects within a feeder impact distribution grid upgrade costs. This study aims to quantify CS impacts on the distribution grid and provide policy and regulatory insights and CS deployment strategies to address them. It is the first analysis that has systematically studied the technical impacts of community solar projects on a wide range of distribution feeders using state-of-the-art optimization and power flow tools. The analysis employs Berkeley Lab’s novel Least-cost Optimal Distribution Grid Expansion (LODGE) model, a deterministic version of the REPAIR model, that optimally upgrades hundreds or even thousands of distribution circuits or feeders. This is the first application of the LODGE model. LODGE finds the least-cost portfolio of traditional distribution system upgrades to integrate CS in combination with alternative solutions, such as utility-owned storage and downsizing CS capacity. Working with a set of least-cost solutions per feeder allows us to benchmark, compare and find techno-economic trends in CS interconnection.

14 SOLAR ENERGY↗

Estimates of the Economic Impacts of Long-Duration, Widespread Power Disruptions in Puerto Rico

A typical electricity customer in Puerto Rico experienced nearly 27 hours of power interruptions in 2023–with many customers experiencing extremely long duration outages during a single event (i.e., greater than one month). This project involved conducting state-of-the-art surveying to assess the direct costs of power outages occurring across Puerto Rico, developing customer-specific models to estimate future costs over varying outage durations, and comparing these estimates to FEMA’s Value of Unit Service for Electricity. We estimate that a territory-wide power outage may cost customers $\$1$, $\$5$ and $\$29$ billion during one-, 14-, and 30-day interruptions, respectively. However, these are lower-bound estimates because our study focused on direct economic costs and, by necessity, did not fully incorporate (1) indirect impacts to the economy; (2) costs to repair or replace damaged utility infrastructure; and (3) the broader societal consequences including increased morbidity- and mortality-related costs. The information contained in this study can be used to estimate the direct economic value of past or proposed investments in power system resilience. We conclude with a discussion of this study’s limitations and suggest additional research to improve stakeholder understanding of the impacts of power outages across Puerto Rico.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Synthetic Scientific Image Generation with VAE, GAN, and Diffusion Model Architectures

Generative AI (genAI) has emerged as a powerful tool for synthesizing diverse and complex image data, offering new possibilities for scientific imaging applications. This review presents a comprehensive comparative analysis of leading generative architectures, ranging from Variational Autoencoders (VAEs) to Generative Adversarial Networks (GANs) on through to Diffusion Models, in the context of scientific image synthesis. We examine each model's foundational principles, recent architectural advancements, and practical trade-offs. Our evaluation, conducted on domain-specific datasets including microCT scans of rocks and composite fibers, as well as high-resolution images of plant roots, integrates both quantitative metrics (SSIM, LPIPS, FID, CLIPScore) and expert-driven qualitative assessments. Results show that GANs, particularly StyleGAN, produce images with high perceptual quality and structural coherence. Diffusion-based models for inpainting and image variation, such as DALL-E 2, delivered high realism and semantic alignment but generally struggled in balancing visual fidelity with scientific accuracy. Importantly, our findings reveal limitations of standard quantitative metrics in capturing scientific relevance, underscoring the need for domain-expert validation. We conclude by discussing key challenges such as model interpretability, computational cost, and verification protocols, and discuss future directions where generative AI can drive innovation in data augmentation, simulation, and hypothesis generation in scientific research.

Generative Adversarial Networks↗

Direct Recycling R&D at the ReCell Center

The expected rapid growth in electric vehicle deployment will inevitably be followed by a corresponding rise in the supply of end-of-life vehicles and their lithium-ion batteries (LIBs). The batteries may be reused, but will eventually be spent and provide a potential domestic resource that can help supply materials for future battery production. However, commercial recycling processes depend on profits from recovery of cobalt, use of which is being reduced in new cathode chemistries. The U.S. Department of Energy, therefore, established the ReCell Center in early 2019 to develop robust LIB recycling technology that would be economical even for batteries that contain no cobalt. The central feature of the technology is recovery of the cathode material with its unique crystalline cathode morphology intact in order to retain its value and functionality. Other materials are recovered as well in order to maximize revenues and minimize waste-handling costs. Analysis and modeling serve to evaluate and compare process options so that we can identify those that will be most economical while still minimizing energy use and environmental impacts. This paper provides background and describes highlights of the center’s first 2 years of operation.

Gaines, Linda (ORCID:0000000237263387)↗

Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations

Abstract. Deep learning (DL) and machine learning (ML) are widely used in hydrological modelling, which plays a critical role in improving the accuracy of hydrological predictions. However, the trade-off between model performance and computational cost has always been a challenge for hydrologists when selecting a suitable model, particularly for probabilistic post-processing with large ensemble members. This study aims to systematically compare the quantile regression forest (QRF) model and countable mixtures of asymmetric Laplacians long short-term memory (CMAL-LSTM) model as hydrological probabilistic post-processors. Specifically, we evaluate their ability in dealing with biased streamflow simulations driven by three satellite precipitation products across 522 nested sub-basins of the Yalong River basin in China. Model performance is comprehensively assessed using a series of scoring metrics from both probabilistic and deterministic perspectives. Our results show that the QRF model and the CMAL-LSTM model are comparable in terms of probabilistic prediction, and their performances are closely related to the flow accumulation area (FAA) of the sub-basin. The QRF model outperforms the CMAL-LSTM model in most sub-basins with smaller FAA, while the CMAL-LSTM model has an undebatable advantage in sub-basins with FAA larger than 60 000 km2 in the Yalong River basin. In terms of deterministic predictions, the CMAL-LSTM model is preferred, especially when the raw streamflow is poorly simulated and used as input. However, setting aside the differences in model performance, the QRF model with 100-member quantiles demonstrates a noteworthy advantage by exhibiting a 50 % reduction in computation time compared to the CMAL-LSTM model with the same ensemble members in all experiments. As a result, this study provides insights into model selection in hydrological post-processing and the trade-offs between model performance and computational efficiency. The findings highlight the importance of considering the specific application scenario, such as the catchment size and the required accuracy level, when selecting a suitable model for hydrological post-processing.

Geology↗

West Africa Battery Energy Storage Systems (BESS) Capacity Building - Discussion of BESS Tariffs: Payment Structures and Case Studies [Slides]

Battery Energy Storage Systems (BESS) are emerging as critical assets for enhancing grid reliability, integrating renewable energy, and enabling system flexibility. Yet, the regulatory and financial frameworks that determine how BESS projects are compensated vary widely across jurisdictions. This presentation explores international case studies - from Honduras, Costa Rica, Chile, South Africa, Mexico, and Brazil - to illustrate how tariff design and payment structures are evolving to support large-scale BESS deployment. The cases highlight a range of ownership and revenue models, including cost-of-service mechanisms, energy and capacity payments, and market-based arbitrage, as well as hybrid approaches under development. The discussion will examine key challenges such as defining remuneration for ancillary services, addressing double charging, and accounting for efficiency losses and degradation over time. By comparing experiences across markets, the presentation identifies emerging best practices for valuing BESS and designing tariffs that align technical performance with economic incentives, providing insights for regulators, utilities, and policymakers pursuing storage integration.

25 ENERGY STORAGE↗

Structural analysis of light aircraft using NASTRAN

An application of NASTRAN to the structural analysis of light aircraft was conducted to determine the cost effectiveness. A model of the Baby Ace D model homebuilt aircraft was used. The NASTRAN model of the aircraft consists of 193 grid points connected by 352 structural members. All members are either rod or beam elements, including bending of unsymmetrical cross sections and torsion of noncircular cross sections. The aerodynamic loads applied to the aircraft were in accordance with FAA regulations governing the utility category aircraft.

Wilkinson, M. T.↗

Control system design using frequency domain models and parameter optimization, with application to supersonic inlet controls

A technique is described for designing feedback control systems using frequency domain models, a quadratic cost function, and a parameter optimization computer program. FORTRAN listings for the computer program are included. The approach is applied to the design of shock position controllers for a supersonic inlet. Deterministic or random system disturbances, and the presence of random measurement noise are considered. The cost function minimization is formulated in the time domain, but the problem solution is obtained using a frequency domain system description. A scaled and constrained conjugate gradient algorithm is used for the minimization. The approach to a supersonic inlet included the calculations of the optimal proportional-plus integral (PI) and proportional-plus-integral-plus-derivative controllers. A single-loop PI controller was the most desirable of the designs considered.

Seidel, R. C.↗

An application of interactive computer graphics technology to the design of dispersal mechanisms

Interactive computer graphics technology is combined with a general purpose mechanisms computer code to study the operational behavior of three guided bomb dispersal mechanism designs. These studies illustrate the use of computer graphics techniques to discover operational anomalies, to assess the effectiveness of design improvements, to reduce the time and cost of the modeling effort, and to provide the mechanism designer with a visual understanding of the physical operation of such systems.

Richter, B. J.↗

An application of interactive computer graphics technology to the design of dispersal mechanisms

Interactive computer graphics technology is combined with a general purpose mechanisms computer code to study the operational behavior of three guided bomb dispersal mechanism designs. These studies illustrate the use of computer graphics techniques to discover operational anomalies, to assess the effectiveness of design improvements, to reduce the time and cost of the modeling effort, and to provide the mechanism designer with a visual understanding of the physical operation of such systems.

Richter, B. J.↗

Millimeter wave communication satellite concepts

Methodology has been developed for identifying viable and appropriate technologies for future NASA millimeter wave research as based upon the technical requirements of potential space communication services. Applicability of the methodology has been verified through its use with two conceptual communications systems. The subsystem cost and weight models are the appropriate level of detail for this study. Application of the methodology to the detailed design of a satellite system would require further model refinement.

Holland, L. D.↗

Fault-tolerant system optimization

The paper describes the decisions to be made in the design of fault-tolerant systems and provides details of a comprehensive model developed to cost optimize such systems. Economical use of replication is making fault-tolerant systems possible and more applications for safety crucial systems such as active flight controls can be expected. In turn, the use of massive redundancy, fault-tolerance, and reconfigurable systems in stimulating the development of new analytical tools for establishing the cost and effectiveness of the safety and cost effectiveness of the levels of replication will increase. Closed-form analytical solutions for the reliability and maintainability analysis of fault-tolerant systems are complex, and Monte-Carlo simulation appears to be a more desirable method of establishing the reliability and maintainability of such systems.

Rose, J.↗

An analytical tool for simulating Large AMplitude Propellant Slosh

The development of a multiple-mass, nonlinear, finite-element analytical model - the Large AMplitude Propellant Slosh model (LAMPS) in two- and three-dimensional versions, is described. The model is used in predicting the forces on the Space Shuttle external tank caused by large amplitude motion of propellant fluid. Comparisons between measured propellant reorientation forces and those predicted by the LAMPS models are presented, and it is concluded that the model provides a cost effective, experimentally verified approach to a complicated nonlinear problem.

Berry, R. L.↗