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At least 1,783 records · Page 99

Understanding Trends in Wind Turbine Prices Over the Past Decade

Taking a bottom-up approach, this report examines seven primary drivers of wind turbine prices in the United States, with the goal of estimating the degree to which each contributed to the doubling in turbine prices from 2002 through 2008, as well as the subsequent decline in prices through 2010 (our analysis does not extend into 2011 because several of these drivers are best gauged on a full-year basis due to seasonality issues). The first four of these drivers can be considered, at least to some degree, endogenous influences – i.e., those that are largely within the control of the wind industry – and include changes in: 1) Labor costs, which have historically risen during times of tight turbine supply; 2) Warranty provisions, which reflect technology performance and reliability, and are most often capitalized in turbine prices; 3) Turbine manufacturer profitability, which can impact turbine prices independently of costs; and 4) Turbine design, which for the purpose of this analysis is principally manifested through increased turbine size. The other three drivers analyzed in this study can be considered exogenous influences, in that they can impact wind turbine costs but fall mostly outside of the direct control of the wind industry. These exogenous drivers include changes in: 5) Raw materials prices, which affect the cost of inputs to the manufacturing process; 6) Energy prices, which impact the cost of manufacturing and transporting turbines; and 7) Foreign exchange rates, which can impact the dollar amount paid for turbines and components imported into the United States.

17 WIND ENERGY↗

Valuing Resilience Benefits of Microgrids for an Interconnected Island Distribution System

Extreme climate-driven events such as hurricanes, floods, and wildfires are becoming more intense in areas exposed to these threats, requiring approaches to improve the resilience of the electrical infrastructure serving these communities. Long-duration outages caused by such high impact events propagate to economic, health, and social consequences for communities. As essential service providers, electric utilities are mandated to provide safe, economical and reliable electricity to their customers. The public is becoming less tolerant to these more frequent disruptions, especially in view of technological advances that are intended to improve power quality, reliability and resilience. One promising solution is state-of-the-art microgrids and the advanced controls employed therein. This paper presents and demonstrates an approach to technoeconomic analysis that can be used to value the avoided economic consequences of grid resilience investments, as applied to the islands of Vieques and Culebra in Puerto Rico. This valuation methodology can support policies to incorporate resilience value into any investment decision-making process, especially those which serve the public interest.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Gravity-improved metastability bounds for the Type-I seesaw mechanism

Right-handed neutrinos (RHN) destabilize the electroweak vacuum by increasing its decay rate. In the SM, the latter is dominated by physics at the RG scale at which λ reaches its minimum, ${\mu}_{\ast}^{\textrm{SM}}$ ~10 17 GeV. For large neutrino Yukawa coupling Y ν , RHNs can push μ* beyond the Planck scale, implying that gravitational effects need to be taken into account. In this work, we perform the first comprehensive study of electroweak vacuum metastability in the type-I seesaw mechanism including these effects. Our analysis covers both low- and high-scale seesaw models, with two as well as three RHNs and for multiple values of the Higgs’ non-minimal coupling to gravity. We find that gravitational effects can significantly stabilize the vacuum, leading to weaker metastability bounds. We show that metastability sets the strongest bounds for low-scale seesaws with M N > 1 TeV. For high-scale seesaws, we find upper bounds on the allowed masses for the RHNs, which are relevant for high-scale leptogenesis. We also point out that Tr(${Y}_{\nu}^{\dagger}$Y ν ), which is commonly used to express these metastability bounds, cannot be used for all of parameter space. Instead, we argue that bounds can always be expressed reliably through Tr(${Y}_{\nu}^{\dagger}$Y ν ${Y}_{\nu}^{\dagger}$Y ν ). Lastly, we use this insight to develop a new technique for an easier RG analysis applicable to scenarios with degenerate RHN masses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Verification of MOOSE/Bison's Heat Conduction Solver Using Combined Spatiotemporal Convergence Analysis

Bison is a computational physics code that uses the finite element method to model the thermo-mechanical response of nuclear fuel. Since Bison is used to inform high-consequence decisions, it is important that its computational results are reliable and predictive. One important step in assessing the reliability and predictive capabilities of a simulation tool is the verification process, which quantifies numerical errors in a discrete solution relative to the exact solution of the mathematical model. One step in the verification process—called code verification—ensures that the implemented numerical algorithm is a faithful representation of the underlying mathematical model, including partial differential or integral equations, initial and boundary conditions, and auxiliary relationships. In this paper, the code verification process is applied to spatiotemporal heat conduction problems in Bison. Simultaneous refinement of the discretization in space and time is employed to reveal any potential mistakes in the numerical algorithms for the interactions between the spatial and temporal components of the solution. For each verification problem, the correct spatial and temporal order of accuracy is demonstrated for both first- and second-order accurate finite elements and a variety of time-integration schemes. Furthermore, these results provide strong evidence that the Bison numerical algorithm for solving spatiotemporal problems reliably represents the underlying mathematical model in MOOSE. The selected test problems can also be used in other simulation tools that numerically solve for conduction or diffusion.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Electrification Futures Study: Scenarios for Demand-Side Adoption in the United States

Electrification - the potential for increased electricity demand due to new services and the shift from any non-electric source of energy to electricity at the point of final consumption - is a major emerging trend in energy markets around the world. Select driving forces for this trend are a collection of newly-improved electric end-use technologies, engaged consumers and manufacturers, and a variety of economic and policy objectives in different jurisdictions. NREL and partners are conducting a multi-year study of electrification scenarios, which will explore research questions related to the potential key technologies for, planning requirements for, and impacts of deep electrification of the U.S. economy. NREL recently published a report that presents scenarios with various degrees of future electrification in all major end-use sectors of the U.S. energy system, and quantifies impacts on the amount and shape of national and regional electricity demand. In addition, ongoing analysis is exploring how the U.S. electricity system could need to transform to meet changes in demand from an electrified economy, the potential role of demand-side flexibility in supporting reliable operations of a clean electricity grid, and the potential costs, benefits, and impacts of mass electrification. This talk will serve to frame some of the overall boundaries of the session and report on electrification levels and impacts under a variety of scenarios.

30 DIRECT ENERGY CONVERSION↗

High-throughput cardiac safety evaluation and multi-parameter arrhythmia profiling of cardiomyocytes using microelectrode arrays

Microelectrode arrays (MEAs) recording extracellular field potentials of human-induced pluripotent stem cell-derived cardiomyocytes (hiPS-CM) provide a rich data set for functional assessment of drug response. The aim of this work is the development of a method for a systematic analysis of arrhythmia using MEAs, with emphasis on the development of six parameters accounting for different types of cardiomyocyte signal irregularities. We describe a software approach to carry out such analysis automatically including generation of a heat map that enables quick visualization of arrhythmic liability of compounds. We also implemented signal processing techniques for reliable extraction of the repolarization peak for field potential duration (FPD) measurement even from recordings with low signal to noise ratios. We measured hiPS-CM's on a 48 well MEA system with 5 minute recordings at multiple time points (0.5, 1, 2 and 4 h) after drug exposure. We evaluated concentration responses for seven compounds with a combination of hERG, QT and clinical proarrhythmia properties: Verapamil, Ranolazine, Flecainide, Amiodarone, Ouabain, Cisapride, and Terfenadine. The predictive utility of MEA parameters as surrogates of these clinical effects were examined. The beat rate and FPD results exhibited good correlations with previous MEA studies in stem cell derived cardiomyocytes and clinical data. The six-parameter arrhythmia assessment exhibited excellent predictive agreement with the known arrhythmogenic potential of the tested compounds, and holds promise as a new method to predict arrhythmic liability. - Highlights: • Six parameters describing arrhythmia were defined and measured for known compounds. • Software for efficient parameter extraction from large MEA data sets was developed. • The proposed cellular parameter set is predictive of clinical drug proarrhythmia.

60 APPLIED LIFE SCIENCES↗

An Operations and Maintenance Roadmap for U.S. Offshore Wind: Enabling a Cost-Effective and Sustainable U.S. Offshore Wind Energy Industry Through Innovative Operations and Maintenance

The United States is currently targeting 30GW of offshore wind to be installed by 2030, and 150GW by 2050. Even considering future turbine sizes, this represents thousands of new turbines installed in a diverse set of environments, each with their unique design, installation, and maintenance challenges. While much can be learned from European and Asian experience with offshore wind over the past two decades, it is important to understand the unique circumstances of the U.S. This document explores operations and maintenance of offshore wind energy, specific to the U.S. and attempts to lay out a roadmap for needed activities to ensure reliability of future installations. The roadmap was informed through dozens of interviews with a wide cross-section of the industry, including representatives from OEMs, owner/operators, service companies, certification agencies, service providers, and researchers. The roadmap first describes the problem by component - blades, drivetrain and nacelle, structures and foundations, and electrical systems - through a look at current practices and opportunities for improvement in the areas of Failure Mode Analysis and Mitigation; Monitoring, Sensing, and Inspection; and Maintenance Execution. Crosscutting areas of Digitalization, Robotics and Automation, Prognostics and Health Management and O&M Optimization, Experimentation and Demonstration, Standardization, and Design Optimization Considering Reliability and O&M are then discussed. Finally, the roadmap summarizes all of these topics with recommendations for short (1-3 years), medium (4-7 years), and long term (8-12 years) activities, with a description of needed public and private sector contributions.

17 WIND ENERGY↗

Major Drivers of Long-Term Distribution Transformer Demand

Distribution transformers, used to step-down medium voltage to service-voltage level for end-use electrical consumption, are currently experiencing major shortages. Utilities are experiencing extended lead times for transformers of up to 2 years (a 4x increase on lead times pre-2022) and prices have gone up by as much as 5-6 times in the past 2 years. Current shortages have been attributed to pent-up post-pandemic demand, workforce shortages and low retention rates, component supply chain challenges, and materials shortages (grain-oriented electrical steel, aluminum, and copper). The supply of this equipment is critical for the reliability and growth of the power system, and in meeting administration climate goals in terms of electrification of demand and the growth of renewable energy. This report details some of the initial analysis conducted by the National Renewable Energy Laboratory (NREL), supported by the Department of Energy's Office of Electricity and Office of Policy, in assessing the long-term demand trends for distribution transformers. Expected increased demand is due to a confluence of not only electrification and renewable energy growth, but also in the context of aging electric infrastructure, increased frequency and severity of extreme weather events, and utility-driven investments in reliability and resiliency of the electricity distribution system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Reducing systematic error in weak lensing cluster surveys

Weak lensing provides an important route toward collecting samples of clusters of galaxies selected by mass. Subtle systematic errors in image reduction can compromise the power of this technique. We use the B-mode signal to quantify this systematic error and to test methods for reducing this error. We show that two procedures are efficient in suppressing systematic error in the B-mode: (1) refinement of the mosaic CCD warping procedure to conform to absolute celestial coordinates and (2) truncation of the smoothing procedure on a scale of 10'. Application of these procedures reduces the systematic error to 20% of its original amplitude. We provide an analytic expression for the distribution of the highest peaks in noise maps that can be used to estimate the fraction of false peaks in the weak-lensing κ-signal-to-noise ratio (S/N) maps as a function of the detection threshold. Based on this analysis, we select a threshold S/N = 4.56 for identifying an uncontaminated set of weak-lensing peaks in two test fields covering a total area of ∼3 deg{sup 2}. Taken together these fields contain seven peaks above the threshold. Among these, six are probable systems of galaxies and one is a superposition. We confirm the reliability of these peaks with dense redshift surveys, X-ray, and imaging observations. The systematic error reduction procedures we apply are general and can be applied to future large-area weak-lensing surveys. Our high-peak analysis suggests that with an S/N threshold of 4.5, there should be only 2.7 spurious weak-lensing peaks even in an area of 1000 deg{sup 2}, where we expect ∼2000 peaks based on our Subaru fields.

79 ASTRONOMY AND ASTROPHYSICS↗

Prospects and Limitations of Predicting Fuel Ignition Properties from Low-Temperature Speciation Data

Using chemical kinetic modeling and statistical analysis, we investigate the possibility of correlating key chemical “markers”–typically small molecules–formed during very lean (φ ~ 0.001) oxidation experiments with near-stoichiometric (φ ~ 1) fuel ignition properties. One goal of this work is to evaluate the feasibility of designing a fuel-screening platform, based on small laboratory reactors that operate at low temperatures and use minimal fuel volume. Buras et al. [Combust. Flame2020,216, 472–484] have shown that convolutional neural net (CNN) fitting can be used to correlate first-stage ignition delay times (IDTs) with OH/HO2 measurements during very lean oxidation in low-T flow reactors with better than factor-of-2 accuracy. In this work, we test the limits of applying this correlation-based approach to predict the low-temperature heat release (LTHR) and total IDT, including the sensitivity of total IDT to the equivalence ratio, φ. We demonstrate that first-stage IDT can be reliably correlated with very lean oxidation measurements using compressed sensing (CS), which is simpler to implement than CNN fitting. LTHR can also be predicted via CS analysis, although the correlation quality is somewhat lower than for first-stage IDT. In contrast, the accuracy of total IDT prediction at φ = 1 is significantly lower (within a factor of 4 or worse). Furthermore, these results can be rationalized by the fact that the first-stage IDT and LTHR are primarily determined by low-temperature chemistry, whereas total IDT depends on low-, intermediate-, and high-temperature chemistry. Oxidation reactions are most important at low temperatures, and therefore, measurements of universal molecular markers of oxidation do not capture the full chemical complexity required to accurately predict the total IDT even at a single equivalence ratio. As a result, we find that φ-sensitivity of ignition delay cannot be predicted at all using solely correlation with lean low-T chemical speciation measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the interplay effects with proton scanning beams in stage III lung cancer

Purpose: To assess the dosimetric impact of interplay between spot-scanning proton beam and respiratory motion in intensity-modulated proton therapy (IMPT) for stage III lung cancer. Methods: Eleven patients were sampled from 112 patients with stage III nonsmall cell lung cancer to well represent the distribution of 112 patients in terms of target size and motion. Clinical target volumes (CTVs) and planning target volumes (PTVs) were defined according to the authors' clinical protocol. Uniform and realistic breathing patterns were considered along with regular- and hypofractionation scenarios. The dose contributed by a spot was fully calculated on the computed tomography (CT) images corresponding to the respiratory phase that the spot is delivered, and then accumulated to the reference phase of the 4DCT to generate the dynamic dose that provides an estimation of what might be delivered under the influence of interplay effect. The dynamic dose distributions at different numbers of fractions were compared with the corresponding 4D composite dose which is the equally weighted average of the doses, respectively, computed on respiratory phases of a 4DCT image set. Results: Under regular fractionation, the average and maximum differences in CTV coverage between the 4D composite and dynamic doses after delivery of all 35 fractions were no more than 0.2% and 0.9%, respectively. The maximum differences between the two dose distributions for the maximum dose to the spinal cord, heart V40, esophagus V55, and lung V20 were 1.2 Gy, 0.1%, 0.8%, and 0.4%, respectively. Although relatively large differences in single fraction, correlated with small CTVs relative to motions, were observed, the authors' biological response calculations suggested that this interfractional dose variation may have limited biological impact. Assuming a hypofractionation scenario, the differences between the 4D composite and dynamic doses were well confined even for single fraction. Conclusions: Despite the presence of interplay effect, the delivered dose may be reliably estimated using the 4D composite dose. In general the interplay effect may not be a primary concern with IMPT for lung cancers for the authors' institution. The described interplay analysis tool may be used to provide additional confidence in treatment delivery.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Automated qualification and analysis of protective spark gaps for DC accelerators

Protective spark gaps are used in the high voltage multiplier column of a 3 MeV DC Accelerator to prevent excessive voltage build-ups. Precise gap of 5 mm is maintained between the electrodes in these spark gaps for obtaining 120 kV± 5 kV in 6 kg/cm{sup 2} SF{sub 6} environment which is the dielectric medium. There are 74 such spark gaps used in the multiplier. Each spark gap has to be qualified for electrical performance before fitting in the accelerator to ensure reliable operation. As the breakdown voltage stabilizes after a large number of sparks between the electrodes, the qualification process becomes time consuming and cumbersome. For qualifying large number of spark gaps an automatic breakdown analysis setup has been developed. This setup operates in air, a dielectric medium. The setup consists of a flyback topology based high voltage power supply with maximum rating of 25 kV. This setup works in conjunction with spark detection and automated shutdown circuit. The breakdown voltage is sensed using a peak detector circuit. The voltage breakdown data is recorded and statistical distribution of the breakdown voltage has been analyzed. This paper describes details of the diagnostics and the spark gap qualification process based on the experimental data. (author)

43 PARTICLE ACCELERATORS↗

Preliminary Safety Analysis for a 400-kW Molten Salt Nuclear Battery

The Molten Salt Nuclear battery (MsNB) is a microreactor based on technology developed and operated at Oak Ridge National Laboratory in the 1960s [1]. But the MsNB has been simplified by removing pumps and valves for improved reliability and safety. The MsNB can safely provide up to 10 MWe of power for up to 10 years and potentially it can be transported by air, truck, and rail thanks due to to its small footprint. A computer model has been developed to represent a prototypical 400-kW MsNB using the ANL system code SAM [2]. The model has been used to produce a reactor thermal-hydraulic performance map and perform analysis of unprotected loss of heat sink accident scenario.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Sorption Behavior of Cationic Radionuclides on Biotite Flakes at pH 5 - 17326

Biotite contained in crystalline rock (granite) is a notable mineral because of its high sorption effects for cationic radionuclides. To date, studies on the sorption effects of rocks have focused on the powder form of minerals. However, the form of a mineral will seriously affect its sorption of radionuclides. This study examined the sorption of Cs, Sr, and Eu by biotite in the flake form. Biotite flakes (5 mm x 6 mm) were prepared for the sorption experiments. The initial concentrations of the tracer ions were set to 1 mM for Sr and Eu and 2 mM for Cs. The sorption experiments for Cs, Sr, and Eu were conducted by mixing 0.6 g of biotite flakes and 6 mL of trace solution at pH 5 for 7 days. As a result, the sorption of tracer ions gradually increased with continuous diffusion into the biotite flakes. The diffusion of the tracer ions into the layer structure of biotite was also observed by secondary ion-microprobe mass spectrometry (SIMS) analysis. The apparent diffusion coefficient of Eu into the biotite flakes was estimated to be 3.0 x 10-12 m{sup 2}/s by applying the experimental data to a theoretical model. This estimated diffusion coefficient is smaller than that for matrix diffusion in granite. Therefore, these diffusion and sorption behaviors may be important factors to consider to more reliably estimate the migration rates of radionuclides in host rock. (authors)

58 GEOSCIENCES↗

Upgrading Limiting Peak-Power Analysis Techniques with Modern Validation and Uncertainty Quantification for the Advanced Test Reactor

Here, this work demonstrates the acceptability of the 2D deterministic transport code, HELIOS, to replace the legacy diffusion code, PDQ, for computing the peak-power performance parameters of the Advanced Test Reactor (ATR). The 95% Confidence Rule, commonly used in the commercial reactor sector, is explored to develop the so-called “reliability factors” which provide statistical confidence that the peak-power limits within the hottest location along a fuel plate, referred to as the hot-stripe, will not be exceeded. Additionally, an alternative “legacy” methodology was explored that attempts to mimic the exact PDQ analysis process used for defining the peak-power limits. The legacy methodology, involves interpolating power between regions at azimuthal boundaries subtending the regions of interest. In order to apply the 95% Confidence Rule, a statistically significant calculation-to-measurement bias must first be established. Unlike the commercial world where thousands of power observations can be collected every cycle using on-line flux mapping instrumentation, the ATR power distribution must be measured during “depressurized” zero-power measurements using fission wires in polyethylene wands. In 2012, fission wire activation data was collected during a flux run in the Advanced Test Reactor – Critical facility. Also to improve statistical validity, archival data from ATR zero power flux runs from 1977, 1986, and 1994 were digitized from scanned reports and used to create new benchmark models. Borrowing from least-squares adjustment methods commonly used for neutron activation spectroscopy, adjusted fission wire powers were calculated for all four datasets. The mean and standard deviation of the bias between a priori calculated and adjusted wire-powers was then taken as the bias and uncertainty used in the 95% Confidence Rule.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Thermal analysis and measurement of a solar pond prototype to study the non-convective zone salt gradient stability

Solar ponds combine solar energy collection with long-term storage and can provide reliable thermal energy at temperature ranges from 50 to 90 °C. A solar pond consists of three distinct zones. The first zone, which is located at the top of the pond and contains the less dense saltwater mixture, is the absorption and transmission region, also known as the upper convective zone (UCZ). The second zone, which contains a variation of saltwater densities increasing with depth, is the gradient zone or non-convective zone (NCZ). The last zone is the storage zone or lower convective zone (LCZ). In this region, the density is uniform and near saturation. The stability of a solar pond prototype was experimentally performed. The setup is composed of an acrylic tube with a hot plate emulating the solar thermal energy input. A study of various salinity gradients was performed based on the Stability Margin Number (SMN) criterion, which is used to satisfy the dynamic stability criterion. It was observed that erosion of the NCZ was accelerated due to mass diffusion and convection in the LCZ. As a result, it can be determined that for this prototype the density of the NCZ is greatly affected as the SMN reaches 1.5.

14 SOLAR ENERGY↗

Statistical Performance Analysis on Approximately 320 Perovskite Single- and Two-Junction Solar Cells and Modules from >30 Global Sources

As perovskite photovoltaics (PV) advance from the laboratory to commercial prototypes, their accurate and reliable performance testing is becoming increasingly important. The well documented dynamic response of perovskite solar cells to an external applied voltage has led to the development of steady-state performance measurement methods; however, these methods have not been widely adopted by the perovskite PV community. A key reason for this is that steady-state measurement methods take tens of minutes to complete, as opposed to conventional "fast" current-voltage (I-V) measurements usually lasting a few seconds. Fast I-Vs arise from a snapshot, almost always not a steady-state condition of the device; however, given their widespread use, the question arises: how do performance parameters of perovskite PV compare when measured with fast I-V and with a steady-state method? We compile results from ca. 320 perovskite PV cells and modules, including single junction, and two-terminal perovskite-perovskite and perovskite-Si tandems, and show that fast I-Vs can provide a useful measure of the open-circuit voltage of the devices, while the short-circuit current and the overall efficiency can be widely misestimated. We discuss implications of these findings on performance testing protocols and propose possible options for fast and accurate testing of perovskite PV.

asymptotic↗

Analyzing Potential Failures and Effects in a Pilot-Scale Biomass Preprocessing Facility for Improved Reliability

This study demonstrates a failure identification methodology applied to a preprocessing facility generating conversion-ready feedstocks from biomass meeting conversion process critical quality attribute (CQA) specifications. Failure Modes and Effects Analysis (FMEA) was used as an industrially relevant risk analysis approach to evaluate a logging residue preprocessing system to prepare feedstock for pyrolysis conversion. Risk evaluations considered both system-level and operation unit-level assessments considering process efficiency, product quality, cost, sustainability, and safety. Key outputs included estimations of semi-quantitative risk scores for each failure, identification of the failure impacts, identification of failure causes associated with material attributes and process parameters, ranking success rates of failure detection methods, and speculation of potential mitigation strategies for decreasing failure risk scores. Results showed that deviations from moisture specifications had cascading consequences for other CQAs along with process safety implications. Failures linked to fixed carbon specifications carried the highest risk scores for product quality and process efficiency impacts. As increased throughput can be inversely related to meeting product quality specifications; achieving throughput and other material-based CQAs simultaneously will likely require system optimization or prioritization based on system economics. Ultimately, this work successfully demonstrates FMEA as a risk analysis approach for other bioenergy process systems.

09 BIOMASS FUELS↗