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At least 793 records · Page 44

Quantitative Systems Pharmacology Models for a New International Cardiac Safety Regulatory Paradigm: An Overview of the Comprehensive In Vitro Proarrhythmia Assay In Silico Modeling Approach

As a relatively new discipline, quantitative systems pharmacology has seen a significant increase in the application and utility of drug development. One area that could greatly benefit from such an approach is in the proarrhythmia assessment of new drugs. The Comprehensive In Vitro Proarrhythmia Assay (CiPA) Initiative is a global public–private partnership project that has developed an integrated approach using mechanistic in silico models for proarrhythmia risk prediction. Progress to date has led to the formation of the International Council on Harmonisation Implementation Working Group to revise regulatory guidelines via the Questions-and-Answers process to address the best practices for proarrhythmia models and how they can impact clinical drug development. This article reviews the CiPA in silico model-development process, focusing on its unique development and validation strategy, and summarizes the lessons learned as consideration points for the ongoing implementation of CiPA-like in silico models in drug development.

60 APPLIED LIFE SCIENCES↗

Viral Dynamic Models During COVID‐19: Are We Ready for the Next Pandemic?

Mathematical models have been used for about 30 years to improve our understanding of virus-host interaction, in particular during chronic infections. During the COVID-19 pandemic, these models have been used to provide insights into the natural history of acute SARS-CoV-2 infection, optimize antiviral treatment strategies, understand factors associated with transmission, and optimize surveillance systems. The impact of modeling has been accelerated by the availability of unprecedented multidimensional immune data from animal and human systems, which enhanced partnerships between experimentalists and theorists and led to exciting new modeling and statistical developments. In this mini review, we examine the lessons learned from the COVID-19 pandemic and discuss the main insights provided by mathematical models of viral dynamics at the different stages of the outbreak. Although we focus on respiratory infection, we also consider the new areas for development in anticipation of future acute infections from new or reemerging pathogens.

59 BASIC BIOLOGICAL SCIENCES↗

The development of poly(vinyl chloride) [PVC] extrusions for a 14,000-ton self-supporting structure for the detection of neutrinos

The NOvA Neutrino Experiment has built a one of a kind self-supporting plastic structure, potentially the largest ever built. The PVC structure serves as a neutrino detector and is composed of 28 individual blocks that measure 15.5 m (51 feet) high by 15.5 m (51 feet) wide by 2.1 m (7 feet) deep. The primary parts in the detector construction are 15.5m (51 foot), 15-cell PVC extrusions. These extrusions from the basis of the detector modules which are laminated together in a crossed pattern to form the individual blocks and then filled with mineral oil based liquid scintillator. The self-supporting nature of the detector places important structural requirements on both the PVC formulation and the extrusions. Block assembly requirements impose narrow geometric tolerances. Due to the method of detecting neutrinos, the extrusions must possess exceptionally high reflectivity over a particular wavelength range. The requirement places additional restrictions on the components of the PVC formulation. Altogether, the PVC extrusions have to maintain important reflectivity characteristics, provide structural support to the detector, and meet relatively tight geometric requirements for assembly. In order to meet these constraints, a custom PVC formulation had to be created and extruded. Here, we describe the purpose and requirements of the NOvA detector leading to the production of our unique PVC extrusion, summarize the R&D process, and discuss the lessons learned.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Multimodel validation of single wakes in neutral and stratified atmospheric conditions

Previous research has revealed the need for a validation study that considers several wake quantities and code types so that decisions on the trade-off between accuracy and computational cost can be well informed and appropriate to the intended application. In addition to guiding code choice and setup, rigorous model validation exercises are needed to identify weaknesses and strengths of specific models and guide future improvements. Here, we consider 13 approaches to simulating wakes observed with a nacelle-mounted lidar at the Scaled Wind Technology Facility (SWiFT) under varying atmospheric conditions. We find that some of the main challenges in wind turbine wake modeling are related to simulating the inflow. In the neutral benchmark, model performance tracked as expected with model fidelity, with large-eddy simulations performing the best. In the more challenging stable case, steady-state Reynolds-averaged Navier–Stokes simulations were found to outperform other model alternatives because they provide the ability to more easily prescribe noncanonical inflows and their low cost allows for simulations to be repeated as needed. Dynamic measurements were only available for the unstable benchmark at a single downstream distance. These dynamic analyses revealed that differences in the performance of time-stepping models come largely from differences in wake meandering. This highlights the need for more validation exercises that take into account wake dynamics and are able to identify where these differences come from: mesh setup, inflow, turbulence models, or wake-meandering parameterizations. In addition to model validation findings, we summarize lessons learned and provide recommendations for future benchmark exercises.

17 WIND ENERGY↗

Integrated distribution system and urban district planning with high renewable penetrations

Recent efforts to reduce energy consumption and greenhouse gas emissions have resulted in the development of sustainable, smart districts with highly energy efficient buildings, renewable distributed energy resources (DERs), and support for alternative modes of transportation. However, there is typically little if any coordination between the district developers and the local utility. Most attention is paid to the district's annual net load and generation without considering their instantaneous imbalance or the connecting network's state. This presents an opportunity to learn lessons from the design of distribution feeders for districts characterized by low loads and high penetrations of DERs that can be applied to the distribution grid at large. The aim of this overview is to summarize current practices in sustainable district planning as well as advances in modeling and design tools for incorporating the power distribution system into the district planning process. Recent developments in the modeling and optimization of district power systems, including their coordination with multi-energy systems and the impact of high penetration levels of renewable energy, are introduced. Sustainable districts in England and Japan are reviewed as case studies to illustrate the extent to which distribution system planning has been considered in practice. Finally, newly developed building-to-grid modeling tools that can facilitate coordinated district and power system design with utility involvement are introduced, along with suggestions for future research directions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Solar Energy Research Institute for India and the United States (SERIIUS): Lessons and Results from a Binational Consortium

This book describes the development, functioning, and results of a successful binational program to promote significant scientific advances in Earth-abundant photovoltaics (PV) and concentrated solar power (CSP), advanced process/manufacturing technologies, multiscale modeling and reliability testing, and analysis of integrated solar energy systems. SERIIUS is a consortium between India and the United States dedicated to developing new solar technologies and assessing their potential impact in the two countries. The consortium consists of nearly 50 institutions including academia, national laboratories, and industry, with the goal of developing significant new technologies in all areas of solar deployment. In addition, the program focused on workforce development through graduate students, post-doctoral students, and an international exchange program. Particular emphasis was placed on the following efforts: creating disruptive technologies in PV and CSP through high-impact fundamental and applied research and development (R&D); identifying and quantifying the critical technical, economic, and policy issues for solar energy development and deployment in India; overcoming barriers to technology transfer by teaming research institutions and industry in an effective project structure; building a new platform for binational collaboration using a formalized R&D project structure, along with effective management, coordination, and decision processes; creating a sustainable network and workforce development program from which to build large collaborations and fostering a collaborative culture and outreach programs. This includes using existing and new methodologies for collaboration based on advanced electronic and web-based communication to facilitate functional international teams. The book summarizes the general lessons learned from these experiences.

14 SOLAR ENERGY↗

Developing Ultrahigh-Resolution E3SM Land Model for GPU Systems

Designing and refactoring complex scientific code, such as the E3SM land model (ELM), for new computing architectures is challenging. This paper presents design strategies and technical approaches to develop a data-oriented, GPU-ready ELM model using compiler directives (OpenACC/OpenMP). We first analyze the datatypes and processes in the original ELM code. Then we present design considerations for ultrahigh-resolution ELM (uELM) development for massive GPU systems. These techniques include the global data-oriented simulation workflow, domain partition, code porting and data copy, memory reduction, parallel loop restructure and flattening, and race condition detection. We implemented the first version of uELM using OpenACC targeting the NVidia GPUs in the Summit supercomputer at Oak Ridge National Laboratory. During the implementation, we developed a software tool (named SPEL) to facilitate code generation, verification, and performance tuning using these techniques. The first uELM implementation for Nvidia GPUs on Summit delivered promising results: 1) over 98% of the ELM code was automatically generated and tuned by scripts. Most ELM modules had better computational performances than the original ELM code for CPUs. The GPU-ready uELM is more scalable than the CPU code on fully-loaded Summit nodes. Example profiling results from several modules are also presented to illustrate the performance improvements and race condition detection. The lessons learned and toolkit developed in the study are also suitable for further uELM deployment using OpenMP on the first US exascale computer, Frontier, equipped with AMD CPUs and GPUs.

Schwartz, Peter↗

Development of Friction Stir Processing for Repair of Nuclear Dry Cask Storage System Canisters

The Nuclear Regulatory Commission has identified chloride-induced stress corrosion cracking (CISCC) of austenitic stainless steel dry cask storage systems (DCSS) as an area of great concern. Friction Stir Processing (FSP) was used to repair laboratory-generated stress corrosion cracking (SCC) in representative stainless steel 304 coupons. Results of this study show FSP is a viable method for repair and mitigation CISCC. This paper highlights lessons learned and developed techniques relative to FSP development for crack repair in sensitized thick section stainless steel 304. These include: development of process parameters, welding at low spindle speed, use of weld power and temperature control and optimization of these controls. NDE and destructive analysis are also presented to demonstrate effectiveness of the developed methods for SCC crack repair.

Friction Stir↗

Lessons from the 2010 Deepwater Horizon Accident in the Gulf of Mexico

The 2010 Deepwater Horizon (DWH) accident in the Gulf of Mexico had many unique aspects to it not seen in previous marine spills. Indeed, research related to the DWH response phase, Natural Resource Damage Assessment, Gulf of Mexico Research Initiative (GoMRI), National Academy of Sciences, US agencies: NOAA, EPA, Fish & Wildlife, DOE, and Coast Guard have made this the most studied marine oil spill in the world. There are many oil biodegradation lessons learned from this experience and these will undoubtedly continue for many years.

Hazen, Terry C.↗

A Simulation-Based Dynamic Approach for External Flooding Analysis in Nuclear Power Plants

All nuclear power plants must consider and evaluate external flooding risks such as local intense precipitation, dam failure, and coastal flooding due to storm surge or tsunami. While these events could challenge off-site power and other plant structure integrity, threaten plant safety systems and components, and limit plant access, they are more than often qualitatively regarded as risk insignificant and screened out from detailed evaluation and quantification. The recent lessons learned from the Fukushima seismic/tsunami initiated nuclear accident (2011), the Fort Calhoun (2011), Vermont Yankee (2013), Arkansas Nuclear One (2013), and St. Luice (2014) flooding events showed otherwise. However, developing an external flood model with traditional event tree/fault tree approach as in a static probabilistic risk assessment (PRA) model could be difficult to accurately represent plant system and component behavior and reliability of manual actions during an ever-progressing flood event. The plant response to external flood may be highly spatial- and time- dependent and subject to the hydrological and hydraulic characteristics of the flood event. Such unique challenges prompt the investigation of using the simulation-based dynamic analysis approaches for external flood risk assessment. Simulation methods can better illustrate the performance of structures, systems, and components during an external flooding event. A general framework to perform a simulation-based dynamic flooding analysis is presented in this paper with the sub-tasks of flood hazard analysis, flood fragility analysis, plant response modeling, safety margin analysis or PRA quantification. A new type of State PRA modeling technique is introduced to incorporate time-related interactions such as those from 3D simulations into a traditional PRA model.

99 GENERAL AND MISCELLANEOUS↗

DevOps Pragmatic Practices and Potential Perils in Scientific Software Development

The DevOps movement, which aims to accelerate the continuous delivery of high-quality software, has taken a leading role in reshaping the software industry. Likewise, there is growing interest in applying DevOps tools and practices in the domains of computational science and engineering (CSE) to meet the ever-growing demand for scalable simulation and analysis. Translating insights from industry to research computing, however, remains an ongoing challenge; DevOps for science and engineering demands adaptation and innovation in those tools and practices. There is a need to better understand the challenges faced by DevOps practitioners in CSE contexts in bridging this divide. To that end, we conducted a participatory action research study to collect and analyze the experiences of DevOps practitioners at a major US national laboratory through the use of storytelling techniques. We share lessons learned and present opportunities for future investigation into DevOps practice in the CSE domain.

97 MATHEMATICS AND COMPUTING↗

Residual symmetries and scalar multiplet vacuum alignment in non-Abelian flavour models

We demonstrate that, upon minimizing a renormalizable, single-scalar potential invariant under a non-Abelian symmetry, special orientations in the associated vacuum alignment of the scalar multiplet correspond to the preservation of a discrete residual flavour symmetry in the broken phase of the theory. Conversely, we show that these special scalar alignments are perturbed when additional Lagrangian operators (e.g. renormalizable, multi-flavon operators and/or effective, higher-dimensional operators) are present that break said residual symmetry, leading to a vacuum reorientation and phenomenological consequences. We therefore construct a one-to-one correspondence principle between broken residual symmetries and vacuum alignment corrections, providing a mechanism to identify (and correct) a subtle but persistent form of phenomenologically relevant fine-tuning embedded in — but often ignored by — most successful non-Abelian flavour models. We first establish this correspondence in a set of toy models based on the S4 permutation symmetry, and then apply the lessons learned to the more realistic A4 Altarelli-Feruglio and ∆(27) Universal Texture Zero models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Bioenergy and biodiversity: Key lessons from the Pan American region

Understanding how large-scale bioenergy production can affect biodiversity and ecosystems is important if society is to meet current and future sustainable development goals. A variety of bioenergy production systems have been established within different contexts throughout the Pan American region, with wide-ranging results in terms of documented and projected effects on biodiversity and ecosystems. The Pan American region is home to the majority of commercial bioenergy production and therefore the region offers a broad set of experiences and insights on both conflicts and opportunities for biodiversity and bioenergy. This paper synthesizes lessons learned focusing on experiences in Canada, the United States, and Brazil, regarding the conflicts that can arise between bioenergy production and ecological conservation, and benefits that can be derived when bioenergy policies promote planning and more sustainable land management systems. Lastly, we propose a research agenda to address priority information gaps that are relevant to biodiversity concerns and related policy challenges in the Pan American region.

09 BIOMASS FUELS↗

Flowing fluid electrical conductivity logging of a deep borehole during and following drilling: estimation of transmissivity, water salinity and hydraulic head of conductive zones

Flowing fluid electrical conductivity (FFEC) logging is a hydrogeologic testing method that is usually conducted in an existing borehole. However, for the 2,500-m deep COSC-1 borehole, drilled at Åre, central Sweden, it was done within the drilling period during a scheduled 1-day break, thus having a negligible impact on the drilling schedule, yet providing important information on depths of hydraulically conductive zones and their transmissivities and salinities. In this paper, we present a reanalysis of this set of data together with a new FFEC logging data set obtained soon after drilling was completed, also over a period of 1 day, but with a different pumping rate and water-level drawdown. Their joint analysis not only results in better estimates of transmissivity and salinity in the conducting fractures intercepted by the borehole, but also yields the hydraulic head values of these fractures, an important piece of information for the understanding of hydraulic structure of the subsurface. Two additional FFEC logging tests were done about 1 year later, and are used to confirm and refine this analysis. Results show that from 250 to 2,000 m depths, there are seven distinct hydraulically conductive zones with different hydraulic heads and low transmissivity values. For the final test, conducted with a much smaller water-level drawdown, inflow ceased from some of the conductive zones, confirming that their hydraulic heads are below the hydraulic head measured in the wellbore under non-pumped conditions. Lastly, the challenges accompanying 1-day FFEC logging are summarized, along with lessons learned in addressing them.

58 GEOSCIENCES↗

Modeling High-Impact Weather and Climate: Lessons From a Tropical Cyclone Perspective

Although the societal impact of a weather event increases with the rarity of the event, our current ability to assess extreme events and their impacts is limited by not only rarity but also by current model fidelity and a lack of understanding of the underlying physical processes. This challenge is driving fresh approaches to assess high-impact weather and climate. Recent lessons learned in modeling high-impact weather and climate are presented using the case of tropical cyclones as an illustrative example. Through examples using the Nested Regional Climate Model to dynamically downscale large-scale climate data the need to treat bias in the driving data is illustrated. Domain size, location, and resolution are also shown to be critical and should be guided by the need to: include relevant regional climate physical processes; resolve key impact parameters; and to accurately simulate the response to changes in external forcing. The notion of sufficient model resolution is introduced together with the added value in combining dynamical and statistical assessments to fill out the parent distribution of high-impact parameters. Finally, through the example of a tropical cyclone damage index, direct impact assessments are resented as powerful tools that distill complex datasets into concise statements on likely impact, and as highly effective communication devices.

climate↗

Investigating the Nexus of Climate, Energy, Water, and Land at Decision-Relevant Scales: The Platform for Regional Integrated Modeling and Analysis (PRIMA)

The Platform for Regional Integrated Modeling and Analysis (PRIMA) is an innovative modeling system developed at Pacific Northwest National Laboratory (PNNL) to simulate interactions among natural and human systems at scales relevant to regional decision making. PRIMA brings together state-of-the-art models of regional climate, hydrology, agriculture, socioeconomics, and energy systems using a flexible coupling approach. The platform can be customized to inform a variety of complex questions and decisions, such as the integrated evaluation of mitigation and adaptation options across a range of sectors. Research into stakeholder decision support needs underpins the platform's application to regional issues, including uncertainty characterization. Ongoing numerical experiments are yielding new insights into the interactions among human and natural systems on regional scales with an initial focus on the energy-land-water nexus in the upper U.S. Midwest. This paper focuses on PRIMA’s functional capabilities and describes some lessons learned to date about integrated regional modeling.

integrated regional modeling↗

Projections of future climate for U.S. national assessments: past, present, future

Climate assessments consolidate our understanding of possible future climate conditions as represented by climate projections, which are largely based on the output of global climate models. Over the past 30 years, the scientific insights gained from climate projections have been refined through model structural improvements, emerging constraints on climate feedbacks, and increased computational efficiency. Within the same period, the process of assessing and evaluating information from climate projections has become more defined and targeted to inform users. As the size and audience of climate assessments has expanded, the framing, relevancy, and accessibility of projections has become increasingly important. This paper reviews the use of climate projections in national climate assessments (NCA) while highlighting challenges and opportunities that have emerged over time. Reflections and lessons learned address the continuous process to understand the broadening assessment audience and evolving user needs. Insights for future NCA development include (1) identifying benchmarks and standards for evaluating downscaled datasets, (2) expanding efforts to gather research gaps and user needs to inform how climate projections are presented in the assessment (3) providing practitioner guidance on the use, interpretation, and reporting of climate projections and uncertainty to better inform decision-making.

Assessment↗

CUPID: The Next-Generation Neutrinoless Double Beta Decay Experiment

We report CUPID is a next-generation tonne-scale bolometric neutrinoless double beta decay experiment that will probe the Majorana nature of neutrinos and discover lepton number violation in case of observation of this singular process. CUPID will be built on experience, expertise and lessons learned in CUORE and will be installed in the current CUORE infra-structure in the Gran Sasso underground laboratory. The CUPID detector technology, successfully tested in the CUPID-Mo experiment, is based on scintillating bolometers of Li 2 MoO 4 enriched in the isotope of interest 100 Mo. In order to achieve its ambitious science goals, the CUPID collaboration aims to reduce the backgrounds in the region of interest by a factor 100 with respect to CUORE. This performance will be achieved by introducing the high efficient α/β discrimination demonstrated by the CUPID-0 and CUPID-Mo experiments, and using a high transition energy double beta decay nucleus such as 100 Mo to minimize the impact of the gamma background. CUPID will consist of about 1500 hybrid heat-light detectors for a total isotope mass of 250 kg. The CUPID scientific reach is supported by a detailed and safe background model based on CUORE, CUPID-Mo and CUPID-0 results. The required performances have already been demonstrated and will be presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗