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At least 379 records · Page 21

In Situ Analysis and Visualization of Fusion Simulations: Lessons Learned

The trends in high performance computing, where far more data can be computed that can ever be stored, have made in situ techniques an important area of research and development. Simulation campaigns, where domain scientists work with computer scientists to run a simulation and perform in situ analysis and visualization are important, and complex undertakings. In this paper we report our experiences performing in situ analysis and visualization on two campaigns. The two campaigns were related, but had important differences in terms of the codes that were used, the types of analysis and visualization required, and the visualization tools used. Further, we report the lessons learned from each campaign.

Kim, Mark B.↗

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↗

Lessons Learned and Scalability Achieved When Porting Uintah to DOE Exascale Systems

A key challenge faced when preparing codes for Department of Energy (DOE) exascale systems was designing scalable applications for systems featuring hardware and software not yet available at leadership-class scale. With such systems now available, it is important to evaluate scalability of the resulting software solutions on these target systems. One such code designed with the exascale DOE Aurora and DOE Frontier systems in mind is the Uintah Computational Framework, an open-source asynchronous many-task (AMT) runtime system. To prepare for exascale, Uintah adopted a portable MPI+X hybrid parallelism approach using the Kokkos performance portability library (i.e., MPI+Kokkos). This paper complements recent work with additional details and an evaluation of the resulting approach on Aurora and Frontier. Results are shown for a challenging benchmark demonstrating interoperability of 3 portable codes essential to Uintah-related combustion research. These results demonstrate single-source portability across Aurora and Frontier with scaling characteristics shown to 3,072 Aurora nodes and 9,216 Frontier nodes. In addition to showing results run to new scales on new systems, this paper also discusses lessons learned through efforts preparing Uintah for exascale systems.

Holmen, John [ORNL] (ORCID:0000000259342641)↗

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.↗

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↗

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↗

Fusion Innovation and the Valley of Death—Lessons from Fission

Over the past several decades, the United States (U.S.) and other countries have done important research and development in advanced nuclear energy technologies, both fission and fusion. The urgency of our current climate, energy, and security needs have prompted a concerted effort by innovators, investors, and the public sector to transition from research and development (R&D) to demonstration and commercialization—to cross the proverbial “valley of death.” The stakes are high: humanity needs clean energy options, and the failure of any promising alternative will lower our odds of success. The process of moving an innovation into use has often been described in phases that begin with early research and end with deployment at scale. Between those two phases lies an area often referred to as the “valley of death” because it can require a long period of time, large investments, and often includes significant challenges related to regulation, standardization, and entering markets already structured around incumbent technologies. What can we learn from recent experience with fission to inform our path forward with fusion? At least five key lessons rise to the top: 1) Set bold targets; 2) Empower the private sector; 3) Engage with regulators and the public; 4) Address costs and markets; and 5) Deliver results. Here, this editorial will consider each of these in turn.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Tutorial: Lessons Learned for Behavior Analysts from Data Scientists

Big data is a computing term used to refer to large and complex data sets, typically consisting of terabytes or more of diverse data that is produced rapidly. The analysis of such complex data sets requires advanced analysis techniques with the capacity to identify patterns and abstract meanings from the vast data. The field of data science combines computer science with mathematics/statistics and leverages artificial intelligence, in particular machine learning, to analyze big data. This field holds great promise for behavior analysis, where both clinical and research studies produce large volumes of diverse data at a rapid pace (i.e., big data). This article presents basic lessons for the behavior analytic researchers and clinicians regarding integration of data science into the field of behavior analysis. We provide guidance on how to collect, protect, and process the data, while highlighting the importance of collaborating with data scientists to select a proper machine learning model that aligns with the project goals and develop models with input from human experts. Here, we hope this serves as a guide to support the behavior analysts interested in the field of data science to advance their practice or research, and helps them avoid some common pitfalls.

42 ENGINEERING↗

Autonomous monitoring of algal biomass: Success stories and lessons learned from long-term field deployment

Autonomous, high-frequency monitoring of outdoor algal ponds is needed to quantify biomass productivity and detect culture decline in environments prone to contamination, grazers, and variable operating conditions. We report successes and lessons learned in translating a laboratory spectroradiometric monitoring approach to a multi-year autonomous field deployment at the Arizona Center for Algae Technology and Innovation (AzCATI). The system measures spectrally resolved pond reflectance by ratioing upwelling radiance from each raceway to simultaneous downwelling sky irradiance using fiber-coupled spectrometers. A physics-based reflectance model (ASHARP) is fit to each spectrum pair to estimate optical parameters, including a biomass-proxy coefficient (C a ) which enables near-real-time tracking of biomass accumulation and culture state at 2–5 min intervals. From May 2022 through September 2025 the platform operated continuously while scaling from two to six raceway ponds. Several strains of algae were monitored successfully, including the high productivity Tetraselmis striata and Picochlorum celeri. Transitioning data acquisition from a Windows laptop to a Raspberry Pi improved uptime from 57% (2022) to ~89% (2024–2025) and enabled routine real-time analysis. Further, we converted relative biomass estimates to absolute ash-free dry weight (AFDW) using experimentally-derived calibrations, providing field-relevant biomass predictions with conservative confidence bounds. These results demonstrate the feasibility of long-term, autonomous optical monitoring for well-mixed open-raceway algal cultivation and provide practical guidance for reliable field operation and scaling.

Katinas, Christopher Michael [Sandia National Labo↗

Lessons from the light of a neutron star merger

The discovery by Advanced LIGO/Virgo of gravitational waves from the binary neutron star merger GW170817, and subsequently by astronomers of transient emission across the electromagnetic spectrum, has initiated a new era of multi-messenger gravitational wave astronomy. Here I summarize the electromagnetic discoveries in the context of theoretical counterpart models and present personal views on the major take-away lessons and outstanding new questions from this watershed event, focused on the implications for nuclear physics. The luminosity and colors of the early optical emission discovered within a day of the merger agree well with predictions for “kilonova” emission, powered by the radioactive decay of light r-process nuclei (atomic mass number A≲140). The transition of the spectral energy distribution to near-infrared wavelengths on timescales of days indicates that inner portions of the ejecta contain heavy r-process nuclei with high UV/optical opacity due to the presence of at least some lanthanide elements (A≳140). The “blue” and “red” ejecta components likely possess distinct origins (e.g. dynamical ejecta, magnetar-powered wind, or accretion disk outflow), with implications for the merger process (e.g. the lifetime of the remnant prior to black hole formation) and fundamental properties of neutron stars. I outline the predicted diversity in the electromagnetic emission of future mergers−observed with different ingoing binary masses and/or viewing angles−discovered in the years ahead as LIGO/Virgo reach design sensitivity.

79 ASTRONOMY AND ASTROPHYSICS↗

Advancing strategic environmental assessment in the offshore oil and gas sector: Lessons from Norway, Canada, and the United Kingdom

Abstract: Strategic environmental assessment (SEA) for offshore oil and gas planning and development is utilized in select international jurisdictions, but the sector has received limited attention in the SEA literature. While the potential benefits of and rationale for SEA are well argued, there have been few empirical studies of SEA processes for the offshore sector. Hence, little is known about the efficacy of SEA offshore, in particular its influence on planning and development decisions. This paper examines SEA practice and influence in three international offshore systems: Norway, Atlantic Canada and the United Kingdom, with the intent to identify the challenges, lessons and opportunities for advancing SEA in offshore planning and impact assessment. Results demonstrate that SEA can help inform and improve the efficacy and efficiency of project-based assessment in the offshore sector, however weak coordination between higher and lower tiers limit SEA's ability to influence planning and development decisions in a broad regional environmental and socioeconomic context. - Highlights: Black-Right-Pointing-Pointer SEA can inform and improve the efficacy and efficiency of project EA offshore Black-Right-Pointing-Pointer Scope and deliverables of SEA offshore often differ from stakeholder expectations Black-Right-Pointing-Pointer Considerable variability in influence of SEA output beyond licensing decisions Black-Right-Pointing-Pointer Sector-based SEA offshore is often too restrictive to generate expected benefits.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

MPC solution for optimal load shifting for buildings with ON/OFF staged packaged units: Experimental demonstration, and lessons learned

Small and medium-sized commercial buildings (SMCB) are significant demand response resources, and it is important to develop grid-responsive control algorithms that exploit those resources and create financial benefits for building owners and HVAC service providers. Furthermore, unlike large-sized commercial buildings, there is an opportunity to have universally applicable control solutions for many SMCBs since those buildings have a consistent HVAC system configuration: SMCBs are commonly served by multiple-staged air conditioning units controlled by their own thermostats. Despite the demand response potential and scalability, however, very few control solutions are available for SMCBs. Typical model predictive control (MPC) and heuristic control approaches for cooling load shifting that lower thermostat setpoints before an electric price jump are suitable mainly for large-sized commercial buildings where a continuous capacity modulation is possible, e.g., via dampers in variable air volume terminal units. However, those approaches can cause undesired, high peaks for SMCBs due to the nature of ON/OFF unit staging and narrow thermostat deadbands. This could discourage the use of advanced grid-responsive controls for SMCBs due to the concern of high demand charges, and has to be resolved. This paper presents a MPC solution that overcomes this challenge. It has a hierarchical MPC structure where an upper level MPC is responsible for electrical load shifting in response to an electric price signal while a lower level MPC is responsible for coordinating compressor stages to eliminate unnecessary peaks and follows the setpoints determined by the upper level MPC. In this work, two one-month, comprehensive laboratory tests have been carried out to demonstrate load shifting and cost savings for the algorithm. Interesting trade-offs between energy efficiency and load flexibility were observed and are discussed, and lessons learned for applying MPCs for SMCBs are also presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluation of integrated daylighting and electric lighting design projects: Lessons learned from international case studies

This article presents and discusses the lessons learned from the monitoring of 25 integrated daylighting and electric lighting international case study projects. The case studies consist of real occupied buildings that have been monitored as part of the International Energy Agency (IEA) SHC Task 61/EBC Annex 77 Programme. The general goal of the case studies was to balance lighting energy use with occupants’ visual and non-visual requirements. This was achieved using innovative solutions for daylighting and electric lighting with advanced controls, but also implementing simple and out-of-the-box strategies. The findings suggest that energy demands for lighting can significantly be reduced by combining sensible daylight provision, efficient lighting sources, and advances in controls. Yet, the effective achievement of project goals requires adequate monitoring, fine-tuning, and verification. The findings also suggest that the adoption of “integrative” lighting – that is, lighting systems that address both visual and non-visual responses – is getting increasingly popular. Catering to non-visual requirements will likely drive further innovation in lighting technology. Currently, there is limited investment available for developing daylighting systems for integrative lighting, and the current related electric strategies often come at the risk of energy rebound effects. Overall, providing daylighting and understanding user requirements are fundamental steps towards achieving quality projects, with potential benefits beyond saving energy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Lessons to be learned from a contentious challenge to mainstream radiobiological science (the linear no-threshold theory of genetic mutations)

There are both statistically valid and invalid reasons why scientists with differing default hypotheses can disagree in high-profile situations. Examples can be found in recent correspondence in this journal, which may offer lessons for resolving challenges to mainstream science, particularly when adherents of a minority view attempt to elevate the status of outlier studies and/or claim that self-interest explains the acceptance of the dominant theory. Edward J. Calabrese and I have been debating the historical origins of the linear no-threshold theory (LNT) of carcinogenesis and its use in the regulation of ionizing radiation. Professor Calabrese, a supporter of hormesis, has charged a committee of scientists with misconduct in their preparation of a 1956 report on the genetic effects of atomic radiation. Specifically he argues that the report mischaracterized the LNT research record and suppressed calculations of some committee members. After reviewing the available scientific literature, I found that the contemporaneous evidence overwhelmingly favored a (genetics) LNT and that no calculations were suppressed. Calabrese's claims about the scientific record do not hold up primarily because of lack of attention to statistical analysis. Ironically, outlier studies were more likely to favor supra-linearity, not sub-linearity. Finally, the claim of investigator bias, which underlies Calabrese's accusations about key studies, is based on misreading of text. Attention to ethics charges, early on, may help seed a counter narrative explaining the community's adoption of a default hypothesis and may help focus attention on valid evidence and any real weaknesses in the dominant paradigm. - Highlights: • Edward J Calabrese has made a contentious challenge to mainstream radiobiological science. • Such challenges should not be neglected, lest they enter the political arena without review. • Key genetic studies from the 1940s, challenged by Calabrese, were found consistent and unbiased. • A 1956 genetics report did not hide estimates and does not need investigation for misconduct. • The scientific record was strong for a no-threshold, linear genetic response to radiation.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Highlighting the complexities of a groundwater pilot study during an avian influenza outbreak: Methods, lessons learned, and select contaminant results

The highly pathogenic avian influenza (H5N2) outbreak in the Midwestern United States (US) in 2015 was historic due to the number of birds and poultry operations impacted and the corresponding economic loss to the poultry industry and was the largest animal health emergency in US history. The U.S. Geological Survey (USGS), with the assistance of several state and federal agencies, aided the response to the outbreak by developing a study to determine the extent of virus transport in the environment. The study goals were to: develop the appropriate sampling methods and protocols for measuring avian influenza virus (AIV) in groundwater, provide the first baseline data on AIV and outbreak- and poultry-related contaminant occurrence and movement into groundwater, and document climatological factors that may have affected both survival and transport of AIV to groundwater during the months of the 2015 outbreak. While site selection was expedient, there were often delays in sample response times due to both relationship building between agencies, groups, and producers and logistical time constraints. This study's design and sampling process highlights the unpredictable nature of disease outbreaks and the corresponding difficulty in environmental sampling of such events. The lessons learned, including field protocols and approaches, can be used to improve future research on AIV in the environment. - Highlights: • Historic 2015 avian influenza outbreak resulted in over 50 million birds destroyed. • Study to determine environmental extent of virus transport logistically challenging. • Challenges included communication, relationship building, and safety protocols. • Temperature, precipitation may have favored virus survival, transport to subsurface.

54 ENVIRONMENTAL SCIENCES↗

How to sustain a CO 2 -thermosiphon in a partially saturated geothermal reservoir: Lessons learned from field experiment and numerical modeling

CO 2 has been proposed as a working fluid for geothermal energy production because of its ability to establish a self-sustaining CO 2 thermosiphon, taking advantage of the strong temperature dependence of CO 2 density. To test the concept of CO 2 heat extraction, in January 2015 a CO 2 thermosiphon was operated at the SECARB Cranfield Site, Cranfield, Mississippi, where a brine-saturated sand at a depth of 3.2 km has been under near continuous CO 2 flood since December 2009 as part of a U.S. Department of Energy demonstration of CO 2 sequestration, resulting in a partially saturated reservoir surrounding a well pair. The lateral distance between the producer and injector was 112 m at reservoir depth, a distance considered pre-commercial in scale, but great enough that thermal breakthrough was still not significant after several years of injection. Instead of producing power with a turbine, heat was extracted heat from recirculated fluid using a heat exchanger and portable chiller. The well field and surface equipment were instrumented to compare field observations with predicted responses from numerical models. Thermosiphon flow could be initiated by venting, but thereafter flow rate steadily declined, indicating that the thermosiphon was not sustainable. To model the system, the capability of T2Well, a fully coupled wellbore/reservoir numerical simulator, was expanded to enable simulation of the entire loop of fluid circulation in the fully-coupled system consisting of the injection/production wells, the reservoir, and the surface devices (heat exchanger, flow-rate regulator etc.). Combined with the newly developed TOUGH2 equation of state module called EOS7CMA, the enhanced T2 Well was used prior to the field experiment to simulate the circulation of a CO 2 -H 2 O-CH 4 mixture in a model geothermal system patterned after the Cranfield demonstration test. The model predicted that a sustainable thermosiphon could be achieved. After the field thermosiphon did not achieve the pre-test prediction of flow rates and thermosiphon sustainability, the numerical model was modified to improve realism and calibrate certain processes; it was then able to reproduce the major phenomena observed in the field. In a series of sensitivity studies, many factors were found that could potentially contribute to the failing of a sustainable thermosiphon. These factors could be categorized as two types: factors that increase the resistance to flow and factors that increase heat loss of the working fluid. In conclusion, the lessons learned can be applied to both future modeling and to achieving CO 2 -based geothermal reservoir exploitation.

15 GEOTHERMAL ENERGY↗

The EGS Collab project: Outcomes and lessons learned from hydraulic fracture stimulations in crystalline rock at 1.25 and 1.5 km depth

With the goal of better understanding stimulation in crystalline rock for improving enhanced geothermal systems (EGS), the EGS Collab Project performed a series of stimulations and flow tests at 1.25 and 1.5 km depths. The tests were performed in two well-instrumented testbeds in the Sanford Underground Research Facility in Lead, South Dakota, United States. The testbed for Experiment 1 at 1.5 km depth contained two open wells for injection and production and six instrumented monitoring wells surrounding the targeted stimulation zone. Four multi-step stimulation tests targeting hydraulic fracturing and nearly year-long ambient temperature and chilled water flow tests were performed in Experiment 1. The testbed for Experiments 2 and 3 was at 1.25 km depth and contained five open wells in an outwardly fanning five-spot pattern and two fans of well-instrumented monitoring wells surrounding the targeted stimulation zone. Experiment 2 targeted shear stimulation, and Experiment 3 targeted low-flow, high-flow, and oscillating pressure stimulation strategies. Hydraulic fracturing was successful in Experiments 1 and 3 in generating a connected system wherein injected water could be collected. However, the resulting flow was distributed dynamically, and not entirely collected at the anticipated production well. Thermal breakthrough was not observed in the production well, but that could have been masked by the Joule-Thomson effect. Shear stimulation in Experiment 2 did not occur - despite attempting to pressurize the fractures most likely to shear - because of the inability to inject water into a mostly-healed fracture, and the low shear-to-normal stress ratio. The EGS Collab experiments are described to provide a background for lessons learned on topics including induced seismicity, the correlation between seismicity and permeability, distributed and dynamic flow systems, thermoelastic and pressure effects, shear stimulation, local geology, thermal breakthrough, monitoring stimulation, grouting boreholes, modeling, and system management.

15 - GEOTHERMAL ENERGY↗