Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “reference model”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,135 records · Page 63

How can an ecosystem approach support integrated management of marine renewable energy? An initial assessment from an environmental point of view

With the increasing installation of marine renewable energy (MRE) devices in areas already subject to multiple anthropogenic activities and environmental changes, it is necessary to develop tools and methods for the integrated management of marine ecosystems. The ecosystem approach is a holistic environmental management method that considers all components of an ecosystem. The ecosystem approach has demonstrated utility in the application to various anthropogenic activities and is relevant for consideration within the context of MRE. Indeed, many of the effects observed on marine ecosystems from those other activities are also applicable to MRE development. This review is an initial assessment where we summarize the potential effects of MRE development on marine ecosystems and propose schematic frameworks for applying the ecosystem approach to MRE. We also provide a non-exhaustive list of commonly used models pertinent to the ecosystem approach and associated with several reference studies. An outline of core questions that can currently be answered using available modeling tools central to the ecosystem approach is provided, along with recommendations for the application of this approach to the MRE context. Further, we identify key knowledge gaps and areas that require additional investigation for meaningful application of the ecosystem approach to MRE development. Our recommendations mainly concern the current limitations of applying the ecosystem approach to concrete cases, such as consolidating knowledge of the effects of MRE on the local environment, the need to obtain fine-scale data, considering effects at different spatiotemporal scales, and, finally, the need for an interdisciplinary vision.

16 TIDAL AND WAVE POWER↗

Thermodynamic analysis of a MEMS based differential scanning calorimeter model

Thin film based differential scanning calorimeter (DSC) was developed and utilized for the study of phase-transition kinetics in protein samples. In this paper, we proposed a MEMS based DSC model. The distance between the sample and reference cell was optimized based on the thermal analysis result. The influence of the response time to the shape of the DSC thermograms and the transition temperature was also studied systematically. Meanwhile, Lumry-Eyring model was used to investigate the relationship between the scanning rate and the transition temperature. The modeling result was verified by the lysozyme denaturation tests. This study provided a pathway for the optimization of MEMS based DSC array and the correction of the DSC thermograms.

47 OTHER INSTRUMENTATION↗

A three-dimensional model of terrain-induced updrafts for movement ecology studies

Abstract Background Spatially explicit simulation models of animal movements through the atmosphere necessarily require a representation of the spatial and temporal variation of atmospheric conditions. In particular, for movements of soaring birds that rely extensively on vertical updrafts to avoid flapping flight, accurate and reliable estimation of the vertical component of wind is critical. The interaction between wind and complex terrain shapes both the horizontal and vertical wind fields, highlighting the need to model the coupling between local terrain features and atmospheric conditions at scales relevant to animal movement. Methods In this work, we propose a new empirical model for estimating the orographic updraft field. The model is developed using computational fluid dynamics simulations of canonical atmospheric conditions over moderately complex terrain. To isolate buoyancy and thermal effects, and focus on terrain-induced effects, we use only simulations of a neutrally stratified atmosphere to develop the model. The model, which we name Engineering Vertical Velocity Estimator (EVVE), is simple to implement and is a function of the underlying terrain elevation map, the desired height above ground level (AGL), and wind conditions at a reference height (80 m). We validate the model with data from the Alaiz mountain (Spain) field campaign. Results Compared to observations, the proposed improved model estimates the updrafts at 120 m AGL with a mean error of 0.11 m/s ( $$\sigma =0.28$$ σ = 0.28 m/s), compared to 0.85 m/s ( $$\sigma =0.58$$ σ = 0.58 m/s) for its baseline. For typical land-based wind turbine hub heights of 80 m AGL, the proposed model has a mean error of 0.04 m/s ( $$\sigma =0.25$$ σ = 0.25 m/s), compared to baseline 0.54 m/s ( $$\sigma =0.45$$ σ = 0.45 m/s) estimations. We illustrate an application of the model in movement ecology by comparing simulated tracks and presence maps of golden eagles ( Aquila chrysaetos ) moving across two distinct landscapes. The tracks and presence maps are obtained using a simple heuristic-based movement model, with the updraft field given by the proposed model and a wind vector-based estimation approach that is currently in wide use in movement ecology studies of raptors and other soaring birds. Conclusions We highlight that movement model results can be sensitive to the underlying orographic updraft model, especially in studies of fine-scale movements in regions of complex topography. We suggest adopting the proposed model rather than the wind vector estimation method for studies of soaring bird movements.

17 WIND ENERGY↗

Sensitivity to Physical and Numerical Aspects of Large-Eddy Simulation of Stratocumulus

Abstract A series of numerical experiments where both physical and numerical model parameters are varied with respect to a reference setup is used to investigate the physics of a stratocumulus cloud and the performance of a large-eddy simulation (LES) model. The simulations show a delicate balance of physical processes with some sensitivities amplified by numerical model features. A strong feedback between cloud liquid, cloud-top radiative cooling, and turbulence leads to slow grid convergence of the turbulent fluxes. For a methodology that diagnoses cloud liquid from conserved variables, small errors in the total water amount result in large liquid water errors, which are amplified by the cloud-top radiative cooling leading to large variations of buoyancy forcing. In contrast, when the liquid–radiation–buoyancy feedback is not present in simulations without radiation, the turbulence structure of the boundary layer remains essentially identical for grid resolutions between 20 and 1.25 m. The present runs suggest that the buoyancy reversal instability significantly enhances the entrainment rate. Even though cloud-top radiative cooling is regarded as a key attribute of stratocumulus, the present simulations suggest that surface fluxes and surface shear significantly contribute to the total turbulent kinetic energy. Turbulence spectra exhibit inertial range scaling away from the confinement effects of the surface and inversion. Fine grid resolution LESs agree with observations, especially with respect to cloud liquid and vertical velocity variance, and exhibit grid convergence without any model tuning or ad hoc model choices.

Matheou, Georgios↗

Computational Efficient Upscaling Methodology for Predicting Thermal Conductivity of Nuclear Waste forms

This study evaluated different upscaling methods to predict thermal conductivity in loaded nuclear waste form, a heterogeneous material system. The efficiency and accuracy of these methods were compared. Thermal conductivity in loaded nuclear waste form is an important property specific to scientific researchers, in waste form Integrated performance and safety code (IPSC). The effective thermal conductivity obtained from microstructure information and local thermal conductivity of different components is critical in predicting the life and performance of waste form during storage. How the heat generated during storage is directly related to thermal conductivity, which in turn determining the mechanical deformation behavior, corrosion resistance and aging performance. Several methods, including the Taylor model, Sachs model, self-consistent model, and statistical upscaling models were developed and implemented. Due to the absence of experimental data, prediction results from finite element method (FEM) were used as reference to determine the accuracy of different upscaling models. Micrographs from different loading of nuclear waste were used in the prediction of thermal conductivity. Prediction results demonstrated that in term of efficiency, boundary models (Taylor and Sachs model) are better than self consistent model, statistical upscaling method and FEM. Balancing the computation resource and accuracy, statistical upscaling is a computational efficient method in predicting effective thermal conductivity for nuclear waste form.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Collaborative Research: Centralized Activities in Support of the Radiative Forcing Model Intercomparison Project (Final Technical Report)

This final technical report summarizes the work accomplished by Atmospheric and Environmental Research in support of the Radiative Forcing Model Intercomparison Project, an international effort to assess sources of error and spread in the radiative forcing calculated by state-of-the-art climate models for historical and future climate studies. Our efforts on this project focused on the performing the line-by-line reference calculations for the gas forcing component of RFMIP. This included enhancing AER's line-by-line radiation model with the latest spectroscopic updates, completing the longwave and shortwave clear-sky high-resolution reference calculations using the line-by-line model, and an initial analysis of the reference calculations.

54 ENVIRONMENTAL SCIENCES↗

Invited Review Article: Physics and Monte Carlo techniques as relevant to cryogenic, phonon, and ionization readout of Cryogenic Dark Matter Search radiation detectors

This review discusses detector physics and Monte Carlo techniques for cryogenic, radiation detectors that utilize combined phonon and ionization readout. A general review of cryogenic phonon and charge transport is provided along with specific details of the Cryogenic Dark Matter Search detector instrumentation. In particular, this review covers quasidiffusive phonon transport, which includes phonon focusing, anharmonic decay, and isotope scattering. The interaction of phonons in the detector surface is discussed along with the downconversion of phonons in superconducting films. The charge transport physics include a mass tensor which results from the crystal band structure and is modeled with a Herring-Vogt transformation. Charge scattering processes involve the creation of Neganov-Luke phonons. Transition-edge-sensor (TES) simulations include a full electric circuit description and all thermal processes including Joule heating, cooling to the substrate, and thermal diffusion within the TES, the latter of which is necessary to model normal-superconducting phase separation. Relevant numerical constants are provided for these physical processes in germanium, silicon, aluminum, and tungsten. Random number sampling methods including inverse cumulative distribution function (CDF) and rejection techniques are reviewed. To improve the efficiency of charge transport modeling, an additional second order inverse CDF method is developed here along with an efficient barycentric coordinate sampling method of electric fields. Results are provided in a manner that is convenient for use in Monte Carlo and references are provided for validation of these models.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Primary transcripts: From the discovery of RNA processing to current concepts of gene expression ‐ Review

The main purpose of this review is to recall for investigators - and in particular students -, some of the early data and concepts in molecular genetics and biology that are rarely cited in the current literature and are thus invariably overlooked. There is a growing tendency among editors and reviewers to consider that only data produced in the last 10–20 years or so are pertinent. However this is not the case. In exact science, sound data and lucid interpretation never become obsolete, and even if forgotten, will resurface sooner or later. In the field of gene expression, covered in the present review, recent post-genomic data have indeed confirmed many of the earlier results and concepts developed in the mid-seventies, well before the start of the recombinant DNA revolution. Human brains and even the most powerful computers, have difficulty in handling and making sense of the overwhelming flow of data generated by recent high-throughput technologies. This was easier when low throughput, more integrative methods based on biochemistry and microscopy dominated biological research. Nowadays, the need for organising concepts is ever more important, otherwise the mass of available data can generate only {sup b}uilding ruins{sup }- the bricks without an architect. Concepts such as pervasive transcription of genomes, large genomic domains, full domain transcripts (FDTs) up to 100 kb long, the prevalence of post-transcriptional events in regulating eukaryotic gene expression, and the 3D-genome architecture, were all developed and discussed before 1990, and are only now coming back into vogue. Thus, to review the impact of earlier concepts on later developments in the field, I will confront former and current data and ideas, including a discussion of old and new methods. Whenever useful, I shall first briefly report post-genomic developments before addressing former results and interpretations. Equally important, some of the terms often used sloppily in scientific discussions will be clearly defined. As a basis for the ensuing discussion, some of the issues and facts related to eukaryotic gene expression will first be introduced. In chapter 2 the evolution in perception of biology over the last 60 years and the impact of the recombinant DNA revolution will be considered. Then, in chapter 3 data and theory concerning the genome, gene expression and genetics will be reviewed. The experimental and theoretical definition of the gene will be discussed before considering the 3 different types of genetic information - the {sup T}riad{sup }- and the importance of post-transcriptional regulation of gene expression in the light of the recent finding that 90% of genomic DNA seems to be transcribed. Some previous attempts to provide a conceptual framework for these observations will be recalled, in particular the {sup C}ascade Regulation Hypothesis{sup }(CRH) developed in 1967–85, and the {sup G}ene and Genon{sup }concept proposed in 2007. A knowledge of the size of primary transcripts is of prime importance, both for experimental and theoretical reasons, since these molecules represent the primary units of the {sup R}NA genome{sup }on which most of the post-transcriptional regulation of gene expression occurs. In chapter 4, I will first discuss some current post-genomic topics before summarising the discovery of the high Mr-RNA transcripts, and the investigation of their processing spanning the last 50 years. Since even today, a consensus concerning the real form of primary transcripts in eukaryotic cells has not yet been reached, I will refer to the viral and specialized cellular models which helped early on to understand the mechanisms of RNA processing and differential splicing which operate in cells and tissues. As a well-studied example of expression and regulation of a specific cellular gene in relation to differentiation and pathology, I will discuss the early and recent work on expression of the globin genes in nucleated avian erythroblasts. An important concept is that the primary transcript not only embodies protein-coding information and regulation of its expression, but also the 3D-structure of the genomic DNA from which it was derived. The wealth of recent post-genomic data published in this field emphasises the importance of a fundamental principle of genome organisation and expression that has been overlooked for years even though it was already discussed in the 1970–80ties. These issues are addressed in chapter 5 which focuses on the involvement of the nuclear matrix and nuclear architecture in DNA and RNA biology. This section will make reference to the Unified Matrix Hypothesis (UMH), which was the first molecular model of the 3D organisation of DNA and RNA. The chapter on the {sup R}NA-genome and peripheral memories{sup }discusses experimental data on the ribonucleoprotein complexes containing pre-mRNA (pre-mRNPs) and mRNA (mRNPs) which are organised in nuclear and cytoplasmic spaces respectively. Finally, {sup O}utlook {sup }will enumerate currently unresolved questions in the field, and will propose some ideas that may encourage further investigation, and comprehension of available experimental data still in need of interpretation. In chapter 8, some propositions and paradigms basic to the authors own analysis are discussed. {sup I}n conclusion{sup }the raison d'être of this review is recalled and positioned within the overall framework of scientific endeavour.

60 APPLIED LIFE SCIENCES↗

Confinement effects on the solvation structure of solvated alkaline metal cations in a single-digit 1T-MoS 2 nanochannel: A first-principles study

Confinement plays an important role in determining ion transport in porous materials, which, in turn, may influence the performance of many energy storage and desalination devices. In this work, we combined density functional theory (DFT) with an implicit solvation model and ab initio molecular dynamics (AIMD) to investigate the effects of nanoconfinement on several solvated alkaline metal cations in a single-digit 1T-MoS 2 nanochannel. Our DFT calculations with a solvation model indicated that cations with stronger hydration energy introduce a higher number of co-intercalated water molecules into the channel, consistent with early experimental observation obtained for MXene (2D transition metal carbide) channels. The predicted optimal water numbers for the cations were then used for AIMD simulations that explicitly include the effects of the solvent. When compared with the cations in bulk solution, our simulations showed that the hydration structure and coordination number (CN) of the solvated cations confined in the MoS 2 channel can be significantly altered. Further, we found that larger cations with weaker hydration energy (K + , Rb + , and Cs + ) exhibited a distinctive CN decrease under confinement, while smaller cations (Li + and Na + ) retained a similar hydration shell as in the bulk solution. More specifically, the hydration shell of large cations (K + , Rb + , and Cs + ) in MoS 2 showed similar features of the coordination angle to the bulk, which suggests the partially broken hydration shell with no geometry change under confinement. Our simulations provided insights into the change of the hydration structure of alkaline metal cations under confinement, which may have important implications on their transport in the 1T-MoS 2 channel.

36 MATERIALS SCIENCE↗

Towards replacement of animal tests with in vitro assays: a gene expression biomarker predicts in vitro and in vivo estrogen receptor activity

High-throughput transcriptomics (HTTr) has the potential to support efforts to reduce or replace some animal tests. In past studies, we described a computational approach utilizing a gene expression biomarker consisting of 46 genes to predict estrogen receptor (ER) activity after chemical exposure in ER-positive human breast cancer cells including the MCF-7 cell line. We hypothesized that the biomarker model could identify ER activities of chemicals examined by Endocrine Disruptor Screening Program (EDSP) Tier 1 screening assays in which transcript profiles of the same chemicals were examined in MCF-7 cells. For the 62 chemicals examined including 5 chemicals examined in this study using RNA-Seq, the ER biomarker model accuracy was 1) 97% for in vitro reference chemicals, 2) 76–85% for guideline uterotrophic assays, and 3) 87–88% for guideline and nonguideline uterotrophic assays. For the same chemicals, these accuracies were similar or slightly better than those of the ToxCast ER model based on 18 in vitro assays. The performance of the ER biomarker model indicates that HTTr interpreted using the ER biomarker correctly identifies active and inactive ER reference chemicals. Finally, as part of the HTTr screening program the approach could rapidly identify chemicals with potential ER bioactivities for additional screening and testing.

60 APPLIED LIFE SCIENCES↗

Modeling of multi-component precipitation and crystallization for zero-liquid-discharge desalination

This study proposes novel ZLD treatment trains that integrate multi-component chemical precipitation and multi-effect evaporative crystallization for efficient brine management. The methodology emphasizes sustainability by integrating CO₂ for chemical precipitation and reducing environmental impact, exemplified with two case studies: produced water that includes industrial waste heat utilization by adopting the emerging vacuum air-gapped membrane distillation (VAGMD) technology, and brackish groundwater that is abundant in sulphate which undergoes treatment by low-salt-rejection reverse osmosis (LSRRO) with interstage chemical precipitation. Here, this study is the first of its kind to simultaneously account for reducing risk of mineral scaling and effective recovery of valuable solids when incorporating VAGMD and LSRRO in ZLD treatment trains. Using Reaktoro and WaterTAP, both Python-based, open-source platforms, we model the recovery of high-purity magnesium, calcium, and sodium salts while optimizing energy consumption and operational efficiency in proposed ZLD pathways for case studies of produced water and brackish desalination brine management. Validation with experimental and reference data confirms the reliability of the models used. In both case studies, the optimized ZLD process achieves recovery rates of 97%, 99%, and 90% for Mg, Ca, and Na, with purities exceeding 99%, and brine volume reduced to less than 4% of the initial feed flow.

3D CT scans↗

Financial Innovation Among the Community Wind Sector in the United States

In the relatively brief history of utility-scale wind generation, the 'community wind' sector - defined here as consisting of relatively small utility-scale wind power projects that are at least partly owned by one or more members of the local community - has played a vitally important role as a 'test bed' or 'proving ground' for wind turbine manufacturers. In the 1980s and 1990s, for example, Vestas and other now-established European wind turbine manufacturers relied heavily on community wind projects in Scandinavia and Germany to install - and essentially field-test - new turbine designs. The fact that orders from community wind projects seldom exceeded more than a few turbines at a time enabled the manufacturers to correct any design flaws or manufacturing defects fairly rapidly, and without the risk of extensive (and expensive) serial defects that can accompany larger orders. Community wind has been slower to take root in the United States - the first such projects were installed in the state of Minnesota around the year 2000. Just as in Europe, however, the community wind sector in the U.S. has similarly served as a proving ground - but in this case for up-and-coming wind turbine manufacturers that are trying to break into the broader U.S. wind power market. For example, community wind projects have deployed the first U.S. installations of wind turbines from Suzlon (in 2003), DeWind (2008), Americas Wind Energy (2008) and later Emergya Wind Technologies (2010),1 Goldwind (2009), AAER/Pioneer (2009), Nordic Windpower (2010), Unison (2010), and Alstom (2011). Just as it has provided a proving ground for new turbines, so too has the community wind sector in the United States served as a laboratory for experimentation with innovative new financing structures. For example, a variation of one of the most common financing arrangements in the U.S. wind market today - the 'partnership flip structure' - was first developed by community wind projects in Minnesota more than a decade ago (and is therefore sometimes referred to as the 'Minnesota flip' model) before being adapted by the broader wind market. More recently, a handful of community wind projects built in the United States over the past year have been financed via new and creative structures that push the envelope of wind project finance in the U.S. - in many cases, moving beyond the now-standard partnership flip structures. These projects include: (1) a 4.5 MW project in Maine that combines low-cost government debt with local tax equity, (2) a 25.3 MW project in Minnesota using a sale/leaseback structure, (3) a 10.5 MW project in South Dakota financed by an intrastate offering of both debt and equity, (4) a 6 MW project in Washington state that taps into 'New Markets Tax Credits' using an 'inverted' or 'pass-through' lease structure, and (5) a 9 MW project in Oregon that combines a variety of state and federal incentives and loans with unconventional equity from high-net-worth individuals. In most cases, these are first-of-their-kind financing structures that could serve as useful examples for other projects - both community and commercial wind alike. This new wave of financial innovation occurring in the community wind sector has been facilitated by policy changes, most of them recent. Most notably, the American Recovery and Reinvestment Act of 2009 ('the Recovery Act') enables, for a limited time, wind power (and other types of) projects to elect either a 30% investment tax credit ('ITC') or a 30% cash grant (the 'Section 1603 grant') in lieu of the federal incentive that has historically been available to wind projects in the U.S. - a 10-year production tax credit ('PTC'). This flexibility, in turn, enables wind power projects to pursue lease financing for the first time - leasing is not possible under the PTC. Because they are based on a project's cost rather than energy generation, the 30% ITC and Section 1603 grant also reduce performance risk relative to the PTC - this, too, is an important enabler of lease financing. Finally, by providing a cash rather than tax incentive, the Section 1603 grant alone reduces (but does not eliminate) the need for tax appetite among project owners. All of these policy changes can be particularly useful to community wind projects, and have helped to support the different financial structures mentioned above. This special report - which is distilled from a longer Berkeley Lab report - briefly describes just two of these innovative new financing structures: the sale/leaseback structure used in Minnesota and the intrastate offering conducted in South Dakota. Readers interested in more detail on these two structures, as well as the other three projects not covered here, are encouraged to reference the full Berkeley Lab report.

17 WIND ENERGY↗

Godiva-IV Dosimetry Exercise 2022 Preliminary Results

Integral Experiment Request (IER) 538 is part of a series of dose characterization and nuclear accident dosimetry (NAD) exercises performed under the Department of Energy (DOE) Nuclear Criticality Safety Program (NCSP). This is the second NAD exercise using the Godiva-IV critical assembly and the third NAD exercise overall. The participating laboratories provided their own dosimeters that were mounted on the Lawrence Livermore National Laboratory (LLNL) BOttle Manikin ABsorption (BOMAB) phantoms and aluminum plates. The BOMABs and plates were placed at two, three, and four meters away from the center of Godiva. Alongside the NADs, there was a LLNL Passive Neutron Spectrometer (PNS), Atomic Weapons Establishment (AWE) PNS, and Y-12 Sphere present to measure the neutron dose from Godiva. Two irradiations were conducted to test the NAD performance from each laboratory and assesses their performance to the DOE-STD-1098-2017 part 515 criteria. Neutron and gamma doses were measured prior to this exercise. This work presents a model for the neutron and gamma dose respectively to serve as the reference value. A code written in C/C++/ROOT was used to fit the measured neutron and gamma dose with the new models. It was assumed that the neutron and gamma doses are proportional to the change in temperature of Godiva after a burst irradiation. Uncertainties for the reference values were calculated using error propagation of the model’s parameters. Preliminary results (within twenty-four hours) and final results were compared for each laboratory. On average of all the participating laboratories, 32% of neutron doses and 78% of gamma doses were outside the DOE standards. One laboratory did not report their dose readings and were not included in this average. There is a bias for a lower neutron dose and a higher gamma dose based on the distribution of results. In comparison with the past Godiva-IV NAD exercise, there is an improvement in neutron dose readings by 20%.

BOttle Manikin ABsorption (BOMAB)↗

Modeling and Simulations for the High Flux Isotope Reactor Cycle 400

A concerted effort over the past few years has been focused on enhancing the core model for the High Flux Isotope Reactor (HFIR), as part of a comprehensive study for HFIR conversion from high-enriched uranium (HEU) to low-enriched uranium (LEU) fuel. At this time, the core model used to perform analyses in support of HFIR operation is an MCNP model for the beginning of Cycle 400, which was documented in detail in a 2005 technical report. A HFIR core depletion model that is based on current state-of-the-art methods and nuclear data was needed to serve as reference for the design of an LEU fuel for HFIR. The recent enhancements in modeling and simulations for HFIR that are discussed in the present report include: (1) revision of the 2005 MCNP model for the beginning of Cycle 400 to improve the modeling data and assumptions as necessary based on appropriate primary reference sources HFIR drawings and reports; (2) improvement of the fuel region model, including an explicit representation for the involute fuel plate geometry that is characteristic to HFIR fuel; and (3) revision of the Monte Carlo-based depletion model for HFIR in use since 2009 but never documented in detail, with the development of a new depletion model for the HFIR explicit fuel plate representation. The new HFIR models for Cycle 400 are used to determine various metrics of relevance to reactor performance and safety assessments. The calculated metrics are compared, where possible, with measurement data from preconstruction critical experiments at HFIR, data included in the current HFIR safety analysis report, and/or data from previous calculations performed with different methods or codes. The results of the analyses show that the models presented in this report provide a robust and reliable basis for HFIR analyses.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Developing a Framework for Reference Cell Standards for PV Resource Applications

Quantifying and predicting electricity production from photovoltaic (PV) systems is based on measured or modeled irradiance data. These solar resource data consist of global horizontal irradiance, global tilted irradiance, direct normal irradiance, and diffuse horizontal irradiance, which are either derived from satellite observations validated against ground-based measurements or directly obtained from ground-based measurements. The ground-based measurements are made using thermopile or photodiode radiometers. For a PV plant, the efficiency of the energy production is verified by comparing measured output with the modeled production, which is computed using either modeled or measured irradiance data. Thus, plant performance assessments typically include the uncertainty of the transposition and, in some cases, decomposition of a given irradiance to convert to the appropriate plane-of-array (POA) irradiance corresponding to the orientation of the PV installation. Additionally, the various types of uncertainty in radiometric measurements or the modeled irradiance and the PV module specifications influence the model results and thereby further increase the uncertainty. An alternative method of assessing the PV system performance has been to use reference cells to measure the "PV resource." When used to calculate PV performance ratios, there are inherent systematic differences between radiometers and reference cells, such as spectral, directional, temperature, time responses, nonstability, and nonlinearity differences. Reference cells tend to mimic the performance and characteristics of a PV module more closely. In this report, a framework is proposed to develop standards that will better quantify and characterize the use of reference cells for PV resource measurements. The measurement from an appropriate reference cell in the POA correlates closely with the plant performance, reduces the number of modeling steps needed to simulate PV performance, and hence reduces the uncertainties of the comparisons. Because technologically matched reference cells and PV modules respond similarly to each wavelength of light that composes the incident solar radiation, the uncertainty associated with the changing spectral distribution of incident radiation during the day and year can be greatly reduced. This will reduce the overall uncertainty in estimated PV performance. The same can be said for the angle-of-incidence effects because the reference cells are deployed in the same POA as the PV module. At that point, the main sources of uncertainty are in modeling the temperature effect differences between the reference cells and the PV module and accounting for the difference between the short-circuit current monitored by the reference cells and max power point current and voltage at which the PV module operates. These sources of uncertainty are also associated with typical irradiance measurements made by pyranometers and pyrheliometers; however, typical irradiance measurements also include uncertainties associated with the spectral mismatch between thermopile or photodiode pyranometers and the PV module, which are minimized with the use of reference cells. To enhance the use of reference cells for resource assessment, we identify the necessary data, characteristics, and calibration methodologies of reference cells and how to standardize the use of these data and methods. Further, as we develop this framework, the classification of reference cells will be essential to provide guidance for selecting PV reference cells appropriate for a specific application. As we address the calibration and sources of uncertainties of reference cells, classification schemes and expected limits of performance with respect to certain parameters become important.

14 SOLAR ENERGY↗

Develop and verify soil/structure interaction for pile/foundation interaction

Phase II of the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) project was used to verify the implementation of a new soil-structure interaction (SSI) model for use within offshore wind turbine modeling software. The REDWIN Macro-element model implemented and verified in this study enables a computationally efficient way to model the linear and nonlinear SSI problem, including hysteretic damping, of a monopile structure. The modeling approach was integrated into several modeling tools and a series of increasingly complex simulations was conducted using the IEA 10MW reference turbine mounted on a monopile support structure to verify the coupling between the tools and the REDWIN Macro-element SSI model. This campaign includes only numerical verification between various software and modeling approaches so no experimental measurements are available. The load cases (LC) considered include: LC1 – static response of the tower and substructure LC2 – frequency and mode-shape analysis of the tower and substructure LC3 – response of the tower and substructure due to wind-only loading LC4 – response of the tower and substructure due to wave-only loading LC5 – response of the tower and substructure due to wind and wave loading. Detailed properties of the modeled system are found in the following reference, “Bergua, Roger, Amy Robertson, Jason Jonkman, and Andy Platt. 2021. "Specification Document for OC6 Phase II: Verification of an Advanced Soil-Structure Interaction Model for Offshore Wind Turbines.” Golden, CO: National Renewable Energy Laboratory. NREL/TP-5000-79938. https://www.nlr.gov/docs/fy21osti/79938.pdf. Details on the results from the OC6 Phase II project can be found in the following reference, “Bergua R, Robertson A, Jonkman J, et al. OC6 Phase II: Integration and verification of a new soil–structure interaction model for offshore wind design.” Wind Energy. 2022;25(5):793-810. doi:10.1002/we.2698

17 WIND ENERGY↗

Industrial IoT cross-layer forensic investigation

Cross-layer forensic investigation is addressed for Industrial Internet of Things (IIoT) device attacks in Critical Infrastructure (CI) applications. The operational motivation for cross-layer investigation is provided by the desire to directly correlate bit-level network anomaly detection with physical layer (PHY) device connectivity and/or status (normal, defective, attacked, etc.) at the time of attack. The technical motivation for developing cross-layer techniques is motivated by (a) having considerable capability in place for Higher-Layer Digital Forensic Information exploitation—real-time network cyberattack and postattack analysis, (b) having considerably less capability in place for Lowest-Layer PHY Forensic Information exploitation—the PHY domain remains largely under exploited, and (c) considering cyber-physical integration as a means to jointly exploit higher-layer digital and lowest-layer PHY forensic information to maximize investigative benefit in IIoT cyber forensics. A delineation of higher-layer digital and lowest-layer PHY elements is provided for the standard network Open Systems Interconnection model and the specific Perdue Enterprise Reference Architecture commonly used in IIoT Industrial Control System/Supervisory Control and Data Acquisition applications. Finally, a forensics work summary is provided for each delineated area based on selected representative publications and provides the basis for presenting the envisioned cross-layer forensic investigation.

97 MATHEMATICS AND COMPUTING↗

Machine-Learning Accelerated Studies of Materials with High Performance and Edge Computing

In the studies of materials, experimental measurements often serve as the reference to verify physics theory and modeling; while theory and modeling provide a fundamental understanding of the physics and principles behind. However, the interactions and cross validation between them have long been a challenge even to-date. Not only that inferring a physics model from experimental data is itself a difficult inverse problem, another major challenge is the orders-of-magnitude longer wall-clock time required to carry out high-fidelity computer modeling to match the timescale of experiments. We envisage that by combining high performance computing, data science, and edge computing technology, the current predicament can be alleviated, and a new paradigm of data-driven physics research will open up. For example, we can accelerate computer simulations by first performing the large-scale modeling on high performance computers and train a machine-learned surrogate model. This computationally inexpensive surrogate model can then be transferred to the computing units residing closely to the experimental facilities to perform high-fidelity simulations at a much higher throughout. The model will also be more amenable to analyzing and validating experimental observations in comparable time scales at a much lower computational cost. Further integration of these accelerated computer simulations with an outer machine learning loop can also inform and direct future experiments, while making the inverse problem of physics model inference more tractable. We will demonstrate a proof-of-concept by using a quantum Monte Carlo application, Dynamical Cluster Approximation (DCA++), to machine-learn a surrogate model and accelerate the study of quantum correlated materials.

Li, Ying Wai↗