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At least 1,567 records · Page 87

Data for Impact of Vertical and Seasonal Variation in Leaf Traits on Simulating Soybean Canopy Photosynthesis via 1D and 3D Modeling

Accurate modeling of photosynthesis is crucial for predicting crop productivity and quantifying the carbon cycle in agroecosystems. Leaf traits are essential inputs for modeling canopy photosynthesis. Yet, many existing models still use fixed plant functional type (PTF)-based values to parameterize leaf traits under a big-leaf or two-big-leaf assumption, neglecting their vertical profiles and seasonal changes. This simplification may introduce significant uncertainties in estimating gross primary productivity (GPP). In this study, we simulated soybean GPP and tested the effects of vertical and seasonal variation in three key leaf photosynthetic traits: the maximum carboxylation rate at 25 °C (Vcmax25), leaf chlorophyll content (LCC), and leaf mass per area (LMA) in the 1D-SCOPE and 3D-Helios models. Weekly field measurements were conducted during the growing season of 2024 to support the simulation. We designed ten leaf trait parameterization schemes by incorporating different combinations of vertical profiles and seasonal changes, while assuming homogeneous canopy architecture in both models. Our results revealed that Vcmax25 vertical and seasonal variation had the strongest influence on simulated GPP in both 1D and 3D models, while LCC and LMA effects were minimal. Particularly, the scheme with an empirically parameterized Vcmax25 profile achieved comparable performance to the scheme with the measured Vcmax25 profile. Both 1D-SCOPE and 3D-Helios accurately modeled GPP (SCOPE: R2 = 0.87, Bias = 0.55 µmol m⁻² s⁻¹; Helios: R2 = 0.9, Bias = 0.22 µmol m⁻² s⁻¹) under the most complex scheme, and their responses to vertical and seasonal variation in leaf traits were consistent, demonstrating the robustness of our findings. Based on our findings, we propose a scalable framework for parameterizing leaf traits to improve GPP simulations. This study contributes to improving the representation of leaf trait dynamics in canopy-level photosynthesis models, potentially enhancing our ability to predict crop productivity and understand agroecosystem carbon dynamics.

Photosynthesis↗

Toward an Understanding of the Environmental and Public Health Impacts of Unconventional Natural Gas Development: A Categorical Assessment of the Peer-Reviewed Scientific Literature, 2009-2015

The body of science evaluating the potential impacts of unconventional natural gas development (UNGD) has grown significantly in recent years, although many data gaps remain. Still, a broad empirical understanding of the impacts is beginning to emerge amidst a swell of research. The present categorical assessment provides an overview of the peer reviewed scientific literature from 2009–2015 as it relates to the potential impacts of UNGD on public health, water quality, and air quality. We have categorized all available original research during this time period in an attempt to understand the weight and direction of the scientific literature. Our results indicate that at least 685 papers have been published in peer-reviewed scientific journals that are relevant to assessing the impacts of UNGD. 84% of public health studies contain findings that indicate public health hazards, elevated risks, or adverse health outcomes; 69% of water quality studies contain findings that indicate potential, positive association, or actual incidence of water contamination; and 87% of air quality studies contain findings that indicate elevated air pollutant emissions and/or atmospheric concentrations. This paper demonstrates that the weight of the findings in the scientific literature indicates hazards and elevated risks to human health as well as possible adverse health outcomes associated with UNGD. There are limitations to this type of assessment and it is only intended to provide a snapshot of the scientific knowledge based on the available literature. However, this work can be used to identify themes that lie in or across studies, to prioritize future research, and to provide an empirical foundation for policy decisions.

03 NATURAL GAS↗

How issue frames shape beliefs about the importance of climate change policy across ideological and partisan groups

We use an experiment to examine whether the way in which climate change is framed affects individuals’ beliefs about its importance as a policy issue. We employ frames that emphasize national security, human rights, and environmental importance about the consequences of climate change. We find no evidence that issue frames have an overall effect on opinions about the importance of climate change policy. We do find some evidence that the effect of issue frames varies across ideological and partisan groups. Most notably, issue frames can lead Republicans and those on the political right to view climate change policy as less important. We conclude by discussing our findings relative to extant literature and considering the implications of our findings for those who seek to address the issue of climate change.

54 ENVIRONMENTAL SCIENCES↗

Misclassification of causes of death among a small all-autopsied group of former nuclear workers: Death certificates vs. autopsy reports

The U.S. Transuranium and Uranium Registries performs autopsies on each of its deceased Registrants as a part of its mission to follow up occupationally-exposed individuals. This provides a unique opportunity to explore death certificate misclassification errors, and the factors that influence them, among this small population of former nuclear workers. Underlying causes of death from death certificates and autopsy reports were coded using the 10 th revision of the International Classification of Diseases (ICD-10). These codes were then used to quantify misclassification rates among 268 individuals for whom both full autopsy reports and death certificates with legible underlying causes of death were available. When underlying causes of death were compared between death certificates and autopsy reports, death certificates correctly identified the underlying cause of death’s ICD-10 disease chapter in 74.6% of cases. The remaining 25.4% of misclassified cases resulted in over-classification rates that ranged from 1.2% for external causes of mortality to 12.2% for circulatory disease, and under-classification rates that ranged from 7.7% for external causes of mortality to 47.4% for respiratory disease. Neoplasms had generally lower misclassification rates with 4.3% over-classification and 13.3% under-classification. A logistic regression revealed that the odds of a match were 2.8 times higher when clinical history was mentioned on the autopsy report than when it was not. Similarly, the odds of a match were 3.4 times higher when death certificates were completed using autopsy findings than when autopsy findings were not used. This analysis excluded cases where it could not be determined if autopsy findings were used to complete death certificates. The findings of this study are useful to investigate the impact of death certificate misclassification errors on radiation risk estimates and, therefore, improve the reliability of epidemiological studies.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Comparing Genome-Wide Association Study Results from Different Measurements of an Underlying Phenotype

Increasing popularity of high-throughput phenotyping technologies, such as image-based phenotyping, offer novel ways for quantifying plant growth and morphology. These new methods can be more or less accurate and precise than traditional, manual measurements. Many large-scale phenotyping efforts are conducted to enable genome-wide association studies (GWAS), but it is unclear exactly how alternative methods of phenotyping will affect GWAS results. In this study we simulate phenotypes that are controlled by the same set of causal loci but have differing heritability, similar to two different measurements of the same morphological character. We then perform GWAS with the simulated traits and create receiver operating characteristic (ROC) curves from the results. The areas under the ROC curves (AUCs) provide a metric that allows direct comparisons of GWAS results from different simulated traits. We use this framework to evaluate the effects of heritability and the number of causative loci on the AUCs of simulated traits; we also test the differences between AUCs of traits with differing heritability. We find that both increasing the number of causative loci and decreasing the heritability reduce a trait's AUC. We also find that when two traits are controlled by a greater number of causative loci, they are more likely to have significantly different AUCs as the difference between their heritabilities increases. When simulation results are applied to measures of tassel morphology, we find no significant difference between AUCs from GWAS using manual and image-based measurements of typical maize tassel characters. This finding indicates that both measurement methods have similar ability to identify genetic associations. These results provide a framework for deciding between competing phenotyping strategies when the ultimate goal is to generate and use phenotype-genotype associations from GWAS.

59 BASIC BIOLOGICAL SCIENCES↗

False Indications of Dose-Response Nonlinearity in Large Epidemiologic Cancer Radiation Cohort Studies; A Simulation Exercise

This study explores the likely prevalence of false indications of dose-response nonlinearity in large epidemiologic cancer radiation cohort studies (A-bomb survivors, INWORKS, Techa River). Reasons: Increasing numbers of tests of nonlinearity are being made in studies. Hypothesized nonlinear dose-response models have been justified to policy makers by analyses that rely in part on isolated findings that could be statistical fluctuations. After removing dose nonlinearity (linearization) by adjusting person-years of observation at each dose category, indications of nonlinearity, necessarily false, were counted in 5,000 randomized replications of six datasets. The average frequency of any false positive for five indicators of nonlinearity tested against a linear null was roughly 25% in Monte Carlo simulations per study, consistent with binomial calculations, increasing to ~50% within 6 studies assessed. Comparable frequencies were found using Akaike's information criterion (AIC) for model selection or multi-model averaging. False above-zero threshold doses were found more than 50% of the time, averaging to 0.05 Gy, consistent with findings in the 6 studies. Such bias, uncorrected, could distort meta-analyses of multiple studies, because meta-analyses can incorporate high P value findings. AIC-based correction for the extra threshold parameter lowered these false occurrences to 8 to 19%. Given the simulation rates, the possibility of false positives might be noted when isolated findings of nonlinearity are discussed in a regulatory context. When reporting a threshold dose with a P value > 0.05, it would be informative to note the expected high false prevalence rate due to bias.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

A Big Problem for Small Earthquakes: Benchmarking Routine Magnitudes and Conversion Relationships with Coda Envelope-Derived Mw in Southern Kansas and Northern Oklahoma

Earthquake magnitudes are widely relied upon measures of earthquake size. Although moment magnitude (M w ) has become the established standard for moderate and large earthquakes, difficulty in reliably measuring seismic moments for small (generally M w <4) earthquakes has meant that magnitudes for these events remain plagued by a patchwork of inconsistent measurement scales. Because of this, magnitudes of small earthquakes and statistics derived from them can be biased. Furthermore, because small earthquakes are much more numerous than large ones, many applications, such as seismic hazard modeling, depend critically on analysis of events characterized by magnitudes other than M w . Therefore, to assess this problem, we apply coda envelope analysis to reliably determine moment magnitudes for a case study of small earthquakes from northern Oklahoma and southern Kansas. Not surprisingly, we find significant differences among M L , m bLg , and M w for M ~2–4 earthquakes examined here. More troublingly, we find that relations designed to convert other magnitudes to M w , which are relied upon for important applications such as seismic hazard analysis, often increase rather than decrease this bias for our dataset. In our case study, we find that converted magnitudes can result in a systematic bias sometimes exceeding 0.5 magnitude units, a difference that typically corresponds to a factor of ~3 in seismicity rate. Moreover, we find a correspondingly large bias in Gutenberg–Richter b-values, controlled primarily by inaccurate magnitude scaling in the conversion relationships. Although this study focuses on a relatively small geographic area, we can expect that similar issues exist with varying severity in other regions. Therefore, magnitudes of small earthquakes and their associated statistics, including seismicity rates and b-values, should be treated with caution.

58 GEOSCIENCES↗

LANL SDAV Visualization Update [Slides]

Xeon Phi (MIC) on Stampede: •To demonstrate the portability of our algorithms, the same code was compiled to the Thrust OpenMP backend (including our own OpenMP implementation of scan) and run on a 2563 particle data set on an Intel Xeon Phi SE10P (MIC) Coprocessor on a single node of Stampede at TACC • PISTON version scales to more cores than running the existing serial algorithms with multiple MPI processes. Titan: • This test problem has ~90 million particles per process. • Due to memory constraints on the GPUs, we utilize a hybrid approach, in which the halos are computed on the CPU but the centers on the GPU. • The PISTON MBP center finding algorithm requires much less memory than the halo finding algorithm but provides the large majority of the speed-up, since MBP center finding takes much longer than FOF halo finding with the original CPU code. In-situ Integration in HACC: • Successfully ran 500 time-step, 512 3 particle simulation on Moonlight using our GPU halo and center finders integrated with HACC in-situ • Completed prototype integration with CosmoTools

97 MATHEMATICS AND COMPUTING↗

Implications of Model Structure and Detail for Utility Planning. Scenario Case Studies using the Resource Planning Model

We examine how model investment decisions change under different model configurations and assumptions related to renewable capacity credit, the inclusion or exclusion of operating reserves, dispatch period sampling, transmission power flow modeling, renewable spur line costs, and the ability of a planning region to import and export power. For all modeled scenarios, we find that under market conditions where new renewable deployment is predominantly driven by renewable portfolio standards, model representations of wind and solar capacity credit and interactions between balancing areas are most influential in avoiding model investments in excess thermal capacity. We also compare computation time between configurations to evaluate tradeoffs between computational burden and model accuracy. From this analysis, we find that certain advanced dispatch representations (e.g., DC optimal power flow) can have dramatic adverse effects on computation time but can be largely inconsequential to model investment outcomes, at least at the renewable penetration levels modeled. Finally, we find that certain underappreciated aspects of new capacity investment decisions and model representations thereof, such as spur lines for new renewable capacity, can influence model outcomes particularly in the renewable technology and location chosen by the model. Though this analysis is not comprehensive and results are specific to the model region, input assumptions, and optimization-modeling framework employed, the findings are intended to provide a guide for model improvement opportunities.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Price-Concentration Relationship in Early Residential Solar Third-Party Markets

The market for residential solar photovoltaic (PV) systems in the United States has experienced tremendous growth over the past decade, with installed capacity more than doubling between 2014 and 2016 alone (SEIA, 2016). As the residential market continues to grow, it prompts new questions about the nature of competition between solar installers and how this competition, or lack thereof, affects the prices consumers are paying. It is often assumed that more competition leads to lower prices, but this is not universally true. For example, some studies have shown that factors such as brand loyalty could lead to a negative relationship between concentration and price in imperfectly competitive markets (Borenstein, 1985; Holmes, 1989). As such, the relationship between prices and market concentration is an open empirical question since theory could predict either a positive or negative relationship. Determining a relationship between prices and market concentration is challenging for several reasons. Most significantly, prices and market structure are simultaneously determined by each other -- the amount of competition a seller faces influences the price they can command, and prices determine a seller's market share. Previous studies have examined recent PV pricing trends over time and between markets (Davidson et al., 2015a; Davidson and Margolis 2015b; Nemet et al., 2016; Gillingham et al., 2014; Barbose and Darghouth 2015). While these studies of solar PV pricing are able to determine correlations between prices and market factors, they have not satisfactorily proven causation. Thus, to the best of our knowledge, there is little work to date that focuses on identifying the causal relationship between market structure and the prices paid by consumers. We use a unique dataset on third-party owned contract terms for the residential solar PV market in the San Diego Gas and Electricity service territory to better understand this relationship. Surprisingly, we find that firms charged higher prices in more competitive markets in our sample. The finding is robust across multiple definitions of firm concentration. There are at least two potential explanations for our findings. First, firms could be conducting entry deterrence strategies. It is possible that firms are acting in a non-competitive way and setting prices lower than they would be otherwise. Setting low prices that are below potential competitors' marginal costs could deter entrants and ensure a larger market share. Second, there could be a group of dominant firms (with a competitive fringe), and the dominant firms may occasionally engage in price wars. If this is true, prices should be lower in more concentrated markets during the price wars (Salinger, 1990). As the rooftop PV market continues to grow, market structure will remain a relevant policy issue in consideration of the potential for rooftop solar to contribute to de-carbonization efforts or other policy objectives. This paper adds to a growing emphasis on understanding supply-side factors in scaling up solar markets in the residential sector. Generally, solar markets have become more competitive over the same time period that solar technology costs decreased. While solar system hard costs have come down, our research suggests that total costs are more nuanced in early solar system TPO markets. Policymakers should consider these findings when designing markets, and have the data needed to make informed decisions.

14 SOLAR ENERGY↗

Load Forecasting in Electric Utility Integrated Resource Planning

Integrated resource planning (IRP) is a process used by many vertically-integrated U.S. electric utilities to determine least-cost/risk supply and demand-side resources that meet government policy objectives and future obligations to customers and, in many cases, shareholders. Forecasts of energy and peak demand are a critical component of the IRP process. There have been few, if any, quantitative studies of IRP long-run (planning horizons of two decades) load forecast performance and its relationship to resource planning and actual procurement decisions. In this paper, we evaluate load forecasting methods, assumptions, and outcomes for 12 Western U.S. utilities by examining and comparing plans filed in the early 2000s against recent plans, up to year 2014. We find a convergence in the methods and data sources used. We also find that forecasts in more recent IRPs generally took account of new information, but that there continued to be a systematic over-estimation of load growth rates during the period studied. We compare planned and procured resource expansion against customer load and year-to-year load growth rates, but do not find a direct relationship. Load sensitivities performed in resource plans do not appear to be related to later procurement strategies even in the presence of large forecast errors. These findings suggest that resource procurement decisions may be driven by other factors than customer load growth. Our results have important implications for the integrated resource planning process, namely that load forecast accuracy may not be as important for resource procurement as is generally believed, that load forecast sensitivities could be used to improve the procurement process, and that management of load uncertainty should be prioritized over more complex forecasting techniques.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Characteristics of Low-Priced Solar Photovoltaic Systems in the United States

Despite impressive recent cost reductions, there is wide dispersion in the prices of installed solar photovoltaic (PV) systems. We identify the most important factors that make a system likely to be low priced (LP). Our sample consists of detailed characteristics for 42,611 small-scale (< 15 kW) PV systems installed in 15 U.S. states during 2013. Using four definitions of LP systems, we compare LP and non-LP systems and find statistically significant differences in nearly all factors explored, including competition, installer scale, markets, demographics, ownership, policy, and system components. Logit and probit model results robustly indicate that LP systems are associated with markets with few active installers; experienced installers; customer ownership; large systems; retrofits; and thin-film, low-efficiency, and Chinese modules. We also find significant differences across states, with LP systems much more likely to occur in some than in others. Our focus on the left tail of the price distribution provides implications for policy that are distinct from recent studies of mean prices. While those studies find that PV subsidies increase mean prices, we find that subsidies also generate LP systems. PV subsidies appear to simultaneously shift and broaden the price distribution. Much of this broadening occurs in a particular location, northern California, which is worthy of further investigation with new data.

14 SOLAR ENERGY↗

Envision Charlotte Project Final Report

The Envision Charlotte Project (EC Project), supported by partners at the Center for Climate and Energy Solutions, the University of North Carolina at Charlotte’s Center for Sustainably Integrated Buildings and Sites and the City of Charlotte, has successfully demonstrated that existing buildings can benefit from operations improvements and low-cost efficiency upgrades, and that behavioral change campaigns can be effectively designed for measurability, longevity and impact. Support from this grant gave Envision Charlotte and its partners the resources and flexibility to demonstrate a variety of approaches to improve coordination with stakeholders in the implementation of programs to reduce the consumption of energy, water and waste. The project team also gained insights into the motivations and abilities that influence stakeholder engagement in sustainability initiatives at multiple levels. Importantly, as this report describes, strong partnerships between nonprofits, industry partners and research institutions can produce tangible impacts and replicable results in building efficiency. Further, building operators working alongside student researchers can form productive relationships that can advance building energy management goals. Key Findings of the EC Project This project focused on advancing solutions to energy efficiency in U.S. commercial buildings. The Building Re-Tuning™ Training (BRT) developed by the U.S. DOE’s Pacific Northwest National Lab (PNNL), designed to detect energy savings opportunities and implement improvements with resources and online tools, provided the starting point for the curriculum developed by stakeholders in the EC Project. Although the project partners encountered some issues with data consistency, the overall project outcomes fell short of the energy savings stated in the original proposal, and the total participating building targets were lower than anticipated, important findings, outcomes and lessons learned were achieved. EC Project grantees observed that the PNNL BRT, as currently written, was not compatible with the skills of average frontline mechanical personnel in the Charlotte region where the grant program was performed. Frontline staff are not, typically, energy managers, engineers or building commissioning agents, but they can play a key role in building performance. As detailed in this report, the grantees therefore focused on changes to the BRT that improved the level of training and competency of the frontline workers in this region. Among the technical observations related to improving the BRT that were observed in the EC Project: centralized facilities management often has an impact on building performance; operators can be overly reliant on service contracts; individual behaviors matter, and technology cannot be viewed as a crutch; current Building Automation Systems (BAS) are often too complex to support building efficiency optimization, but BAS coupled with appropriate training can support better outcomes; the “perfectly optimized” building is not a near-term possibility, but better education, especially of executives and managers, on the role of behavioral intervention is a promising direction the building science community can and should pursue; a lack of standards and protocols, and competition between proprietary software from service contracts, remain challenges for this industry. These technical observations, in turn, informed the EC Project’s overall findings, which were: Accomplishing building efficiency is a process of education for all involved in the building design, construction and operation supply chain. Building operators, as a professional class, have an opportunity for further training and education that will lead to better on-the-job performance. An updated Building Re-Tuning™ Training curriculum, based on the findings of this report, could be an avenue for these operators’ professional development.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Potential Impacts of Accelerated Climate Change (Annual Report of Work)

This research project is part of the U.S. Nuclear Regulatory Commission’s (NRC’s) Probabilistic Flood Hazard Assessment (PFHA) research plan in support of developing a risk-informed licensing framework for flood hazards and design standards at proposed new facilities and significance determination tools for evaluating potential deficiencies related to flood protection at operating facilities. The PFHA plan aims to build upon recent advances in deterministic, probabilistic, and statistical modeling of extreme precipitation events to develop regulatory tools and guidance for NRC staff with regard to PFHA for nuclear facilities. The tools and guidance developed under the PFHA plan will support and enhance the NRC’s capacity to perform thorough and efficient reviews of license applications and license amendment requests. They will also support risk-informed significance determination of inspection findings, unusual events, and other oversight activities. For Year 1, specifically, Pacific Northwest National Laboratory (PNNL) staff: Prepared an annual report that summarizes recent scientific findings, reports on activities of federal agencies with direct responsibility for climate change science, and provide a qualitative assessment of these findings relevant to NRC concerns on a regional level (i.e., increasing air and water temperatures, decreasing water availability, increasing frequency and intensity of storms and flooding, and sea level rise). Participated in annual webinars with NRC staff at NRC Headquarters in Rockville, Maryland. Presented updates summarizing recent scientific findings at the NRC PFHA Workshop Headquarters in Rockville, Maryland. PNNL staff have identified neither technical nor programmatic issues in proceeding with Year 2 activities. PNNL staff updated this report in March and April 2019.

54 ENVIRONMENTAL SCIENCES↗

Defending the Homeland: Growing Foreign Challenges to the U.S. Missile Defense Posture

The Office of the Secretary of Defense (OSD) for Policy requested that Lawrence Livermore National Laboratory conduct a Congressionally directed study on homeland missile defense, pursuant to Section 1692 of the fiscal year 2020 National Defense Authorization Act. In accordance with the statutory language, this study considers whether the security benefits obtained by deployment of homeland missile defenses of the United States are undermined or counterbalanced by adverse reactions of potential adversaries, and considers the effectiveness of homeland missile defense efforts of the United States to deter the development of ballistic missiles. Almost a half-century has elapsed since the United States and the Soviet Union signed the Anti-Ballistic Missile (ABM) Treaty, and almost two decades since the former withdrew. Since withdrawing, the United States has sought to develop and deploy a layered missile defense system to defend against regional threats to U.S. and allied interests abroad and to counter limited threats to the U.S. homeland. As such, missile defense supports key national defense policy objectives. Protecting the U.S. homeland, forces abroad, allies, and partners. Deterring attacks against the United States, its allies, and partners. Assuring allies an strengthening U.S. diplomatic activities in peacetime and crisis. We offer five key findings: 1. The primary benefit of the Ground-based Midcourse Defense (GMD) system is the protection it provides the U.S. homeland against a limited but evolving rogue-state missile threat. While this system has never been tested in combat, it appears thus far to have effectively paced North Korea’s development and deployment of intercontinental ballistic missiles (ICBMs). In the absence of such a defensive capability, the United States would likely have been more heavily exposed to North Korean actions, would have operated at a much higher-risk posture, and would have had less negotiating room with which to navigate coercive tactics and crises. Its allies would have been more concerned about U.S. willingness in time of crisis and war to run the risks of protecting them. The GMD system also serves as a hedge against Iranian breakout. 2. Potential adversaries continue to develop long-range ballistic missiles despite deployment of a U.S. homeland missile defense system. This includes both rogue states and major power rivals whose long-range missile programs predated the deployment of U.S. missile defenses. While North Korea has continued its long-range missile developments and achieved an intercontinental capability, Iran has not yet reached this threshold. The broader proliferation of long-range missiles anticipated in the late 1990s has not materialized. 3. While Russia has used the existence of a U.S. homeland missile defense system as a justification for its substantial and continuing weapon modernization program, neither Russian force modernization nor the limited U.S. homeland missile defense system has altered the strategic balance. Russia has long considered U.S. missile defenses—both theater and homeland—as directed against its strategic forces and as a capability that could rapidly advance, thereby eroding Russian confidence in its nuclear deterrent. Russia’s political and military actions appear excessive and negatively impact areas such as arms control, but they do not undermine the primary benefit of the U.S. system cited in Key Finding 1. 4. China’s expansion and diversification of nuclear and missile forces has been influenced by its concerns about U.S. homeland missile defense, but those concerns are only one of many factors in China’s force planning. Although China’s actions to preserve and expand its assured retaliation prospects have not fundamentally altered the strategic balance, its buildup and lack of transparency about its force modernization goals are troubling. Taken together, the aggregate pattern of China’s modernization activities over the past two decades strongly suggests a concerted effort to develop a modern military force commensurate with its intended geopolitical status. Whatever China’s legacy concerns over the survivability of its strategic nuclear forces, its ability to overwhelm the GMD system appears intact today and will be further strengthened in the years ahead as it continues its long-term modernization program. China’s political and military actions negatively affect U.S. security interests but do not undermine the primary benefit of the U.S. system cited in Key Finding 1. 5. The basic finding that benefits have not so far been undermined by adverse reactions is a function of circumstances that are increasingly in flux. The existing GMD-centered system is under increasing pressure from the pace and scope of North Korean missile deployments. The proposed “layered” system seeks to mitigate this impending capability gap in the near term and to complement future capabilities, such as the Next Generation Interceptor, when they come online. Given the pace of U.S. missile defense developments since 2000, it is possible that adversary advances in capability will outpace the U.S. system’s ability to adapt. Additionally, because this layered system is in principle more readily scaled, it will almost certainly be viewed skeptically by China and Russia. In a context of growing great-power security competition, the Department of Defense (DoD) should consider undertaking a broader net assessment of the U.S., Russian, and Chinese force balance.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

U.S. Industrial and Commercial Motor System Market Assessment Report Volume 1: Characteristics of the Installed Base

Motor systems are an integral part of our industrial and commercial facilities. They provide the motive force behind the fans, pumps, compressors, chillers, and conveyors in these facilities. Given their centrality to any facility’s operations, they are a critical energy end use to understand, particularly when developing technologies and policies to meet sustainability goals, improve productivity, and enhance resilience. In the late 1990s, the U.S. Department of Energy (DOE) conducted two seminal studies to better understand the installed stock and energy savings opportunities of industrial and commercial motor systems. In the industrial sector, The United States Industrial Electric Motor Systems Market Opportunities Assessment used primary data collected through onsite assessments and led to a greater understanding of the installed base of motor systems, their characteristics, and the opportunities for energy savings (U.S. Department of Energy, 2002). Notable findings included the following: Industrial motor systems consumed 679 billion kilowatt-hours (kWh) in 1994, representing 23 percent of U.S. electricity consumption. Cost-effective energy efficiency measures could result in 62-104 billion kWh of energy savings annually. Sixty-two percent of the energy savings potential was from fan, pump, and compressor end use equipment. Nearly half of motor system electricity consumption was attributable to approximately 3,500 facilities, or 1.5 percent of U.S. manufacturing facilities. Opportunities for Energy Savings in the Residential and Commercial Sectors with High Efficiency Electric Motors provided an evaluation of the installed stock of motor driven equipment in U.S. commercial and residential buildings and opportunities for utilization of high efficiency motors and variable speed technologies (Arthur D. Little, 1999). Notable findings included the following: Commercial motor systems consumed 343 billion kWh in 1995, with refrigeration and space conditioning constituting 93 percent of the total. Cost-effective energy efficiency measures could result in 51 billion kWh of energy savings annually. Due in no small part to these seminal studies, motor system technologies and usage characteristics have changed drastically since the late 1990s. Greater awareness of cost-effective strategies for reducing motor system electricity consumption have been developed and deployed. This includes several software tools, literature, and utility and government programs promoting energy efficiency improvements in motor driven systems. Additionally, several rounds of energy efficiency standards have been enacted, resulting in improved installed motor efficiency. The cost of variable speed drives has dropped substantially, and combined with utility rebate programs, has led to their greater adoption. Further, since these results were published, the U.S. manufacturing sector has undergone a massive transformation. Due to global competition, some sectors have relocated operations overseas. Others have brought operations onshore to avail low cost and abundant natural gas. Additionally, automation and robotics have pervaded the entire sector. Consequently, these two reports likely do not represent the current state of motor driven systems in U.S. industrial and commercial facilities. As cited in recent studies, the lack of current information on motor system electricity consumption and use characteristics limits the ability to conduct analysis on energy savings potential, develop technologies to address energy and productivity gaps, and develop programs to promote energy efficiency practices and technologies for motor systems (International Energy Agency, 2007; UNIDO, 2010; McKane and Hasanbeigi, 2011; Waide and Brunner, 2011). Specifically, the lack of information affects a range of stakeholders: Governments must rely on outdated information when setting research agendas, developing policies, and designing energy efficiency programs and offerings. Utilities and energy efficiency programs cannot identify the current market needs or potential impact when designing rebate and energy efficiency programs. Electric grid planners cannot identify motor system usage characteristics when developing plans to support the resilience of the electric grid. Manufacturers of motors, motor driven equipment, and drives are hampered when developing technologies to meet the needs of their market. Motor system end users are limited in their ability to identify energy saving opportunities within their own facilities because they do not have reliable benchmark information. In response to the lack of current information and analysis on industrial and commercial motor systems, the DOE initiated an update to these two studies. Launched in 2016 and led by Lawrence Berkeley National Laboratory (LBNL), the Motor System Market Assessment (MSMA) provides an updated, more comprehensive assessment of the installed stock of motor systems in both the industrial and commercial sectors, a review of the supply chains supporting motor and drives in the U.S., and the performance improvement opportunity available from using best available technologies and maintenance and operation practices. The outcomes of the MSMA are documented in three U.S. Industrial and Commercial Motor System Market Assessment reports, with this report being the first listed: 1. Volume 1: Characteristics of the Installed Base (this report) documents the findings on the installed base of motor systems in the U.S. industrial and commercial sectors. Quantification of energy savings potential is not documented in this report but in Volume 3. 2. Volume 2: Motors and Drives Supply Chain Review reviews the state of supply chains for motors and drives installed in U.S. industrial and commercial facilities, focusing on advanced motor and drive technologies and their constituent materials. 3. Volume 3: Energy Savings Opportunity analyzes the energy performance improvement opportunity for the installed base of U.S. industrial and commercial motor systems. This report has been prepared as a reference for motor system stakeholders. It provides factual information as could be best determined by the assessment results and avoids speculating on any findings.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Understanding and Overcoming Water-induced Interfacial Degradation in Si Modules (Final Technical Report)

Moisture ingress is an established issue for photovoltaic module durability. Durability studies probing moisture effects typically evaluate performance losses at the module level, attributing global power losses to the overall humidity condition of the test environment while leaving local module behavior unknown. This project successfully develops an in situ short-wave infrared probe of moisture content in PV modules with demonstrated detection limits better than 100 ppm in EVA-encapsulated Al-BSF and PERC architectures (66 µg/cm3) and applicability across the range of terrestrial conditions. Combining this optical moisture quantification method (water reflectometry detection, WaRD) with peel testing of interfaces, biased photoluminescence imaging of performance, and first principles computation, we correlate module moisture content and cell performance over the course of accelerated damp heat tests. By performing multi-level humidity and thermal accelerated testing over thousands of hours (0, 65 and 85% RH and 25, 65, and 85°C), we are able to attribute effects of individual environmental stresses and the dependence on module architecture. Using first-principles computational chemistry, we find that the decomposition of EVA to acetic acid (Norrish II) is thermodynamically preferred over a pathway to acetaldehyde (Norrish I), elucidating the underlying chemistry of encapsulant degradation. We also find it is likely that water segregates to the stable interfaces of the cell, especially the SiNx/EVA interface. We find that moisture is strongly correlated with reduction in adhesion at the interfaces of the cells, particularly at Ag fingers. We show uniquely that the peel strength required to delaminate the encapsulant from the front of the cell depends not only on the exposure to a high heat and humid environment, but also to the moisture content during the mechanical testing, indicating an important interaction between when mechanical stresses are faced in terms of the moisture content of the module and its durability. We find that the background sheet resistance (that is, the sheet resistance rise not attributable to finger interruptions or cracks) is substantially higher in the backsheet mini-modules vs glass-glass packages when humidity and temperature are faced. This increase in power loss due to the background resistance increase over time in damp heat in glass-backsheet modules resulted in ~3-4% larger decrease in relative PCE compared to glass-glass modules. In glass-backsheet modules, the effect of the moisture dose alone is comparable or greater than that of the combined temperature and water term, suggesting that glass-backsheet modules are overall more susceptible to moisture induced performance loss. Finally, we show that thin film PV modules are amenable to WaRD measurement, based on the ability to detect moisture in POE encapsulants or in the cell stack itself. The ease of WaRD measurement and its few requirements on the bill of materials should enable broad applicability of this technique for studying the effects of moisture in PV.

14 SOLAR ENERGY↗

SAGE Intrusion Detection System: Sensitivity Analysis Guided Explainability for Machine Learning.

This report details the results of a three-fold investigation of sensitivity analysis (SA) for machine learning (ML) explainability (MLE): (1) the mathematical assessment of the fidelity of an explanation with respect to a learned ML model, (2) quantifying the trustworthiness of a prediction, and (3) the impact of MLE on the efficiency of end-users through multiple users studies. We focused on the cybersecurity domain as the data is inherently non-intuitive. As ML is being using in an increasing number of domains, including domains where being wrong can elicit high consequences, MLE has been proposed as a means of generating trust in a learned ML models by end users. However, little analysis has been performed to determine if the explanations accurately represent the target model and they themselves should be trusted beyond subjective inspection. Current state-of-the-art MLE techniques only provide a list of important features based on heuristic measures and/or make certain assumptions about the data and the model which are not representative of the real-world data and models. Further, most are designed without considering the usefulness by an end-user in a broader context. To address these issues, we present a notion of explanation fidelity based on Shapley values from cooperative game theory. We find that all of the investigated MLE explainability methods produce explanations that are incongruent with the ML model that is being explained. This is because they make critical assumptions about feature independence and linear feature interactions for computational reasons. We also find that in deployed, explanations are rarely used due to a variety of reason including that there are several other tools which are trusted more than the explanations and there is little incentive to use the explanations. In the cases when the explanations are used, we found that there is the danger that explanations persuade the end users to wrongly accept false positives and false negatives. However, ML model developers and maintainers find the explanations more useful to help ensure that the ML model does not have obvious biases. In light of these findings, we suggest a number of future directions including developing MLE methods that directly model non-linear model interactions and including design principles that take into account the usefulness of explanations to the end user. We also augment explanations with a set of trustworthiness measures that measure geometric aspects of the data to determine if the model output should be trusted.

97 MATHEMATICS AND COMPUTING↗