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At least 973 records · Page 54

Path-Integrated Stereo X-Ray Digital Image Correlation: Resolving the Violation of Conservation of Intensity

In this study, x-ray imaging addresses many challenges with visible light imaging in extreme environments, where optical diagnostics such as digital image correlation (DIC) and particle image velocimetry (PIV) suffer biases from index of refraction changes and/or cannot penetrate visibly occluded objects. However, conservation of intensity—the fundamental principle of optical image correlation algorithms—may be violated if ancillary components in the X-ray path besides the surface or fluid of interest move during the test. The test series treated in this work sought to characterize the safe use of fiber-epoxy composites in aerospace and aviation industries during fire accident scenarios. Stereo X-ray DIC was employed to measure test unit deformation in an extreme thermal environment involving a visibly occluded test unit, incident surface heating to temperatures above 600°C, and flames and soot from combusting epoxy decomposition gasses. The objective of the current work is to evaluate two solutions to resolve the violation of conservation of intensity that resulted from both the test unit and the thermal chamber deforming during the test. The first solution recovered conservation of intensity by pre-processing the path-integrated X-ray images to isolate the DIC pattern of the test unit from the thermal chamber components. These images were then correlated with standard, optical DIC software. The second solution, called Path-Integrated Digital Image Correlation (PI-DIC), modified the fundamental matching criterion of DIC to account for multiple, independently-moving components contributing to the final image intensity. The PI-DIC algorithm was extended from a 2D framework to a stereo framework and implemented in a custom DIC software. Both solutions accurately measured the cylindrical shape of the undeformed test unit, recovering radii values of R = 76.20±0.12 mm compared to the theoretical radius of R theor = 76.20 mm. During the test, the test unit bulged asymmetrically as decomposition gasses pressurized the interior and eventually burned in a localized jet. Both solutions measured the heterogeneous radius of this bulge, which reached a maximum of approximately R = 91 mm, with a discrepancy of 2–3% between the two solutions. Two solutions that resolve the violation of conservation of intensity for path-integrated X-ray images were developed. Both were successfully employed in a stereo X-ray DIC configuration to measure deformation of an aluminum-skinned, fiber-epoxy composite test unit in a fire accident scenario.

47 OTHER INSTRUMENTATION↗

Effects of Strain and Strain Rate on Dynamic Grain Growth and Subgrain Evolution During Plastic Deformation of an Interstitial-Free Steel at 850 ° C

Here, the effects of strain and strain rate on dynamic grain growth (DGG) and subgrain evolution are reported for an interstitial-free steel deformed at 850 ° C. Microstructures produced during tension tests at true-strain rates of 10 -4 and to 10 -3 s -1 true strains ranging from 0.02 to 0.2 were preserved following deformation. These were characterized using electron backscatter diffraction (EBSD), including the application of spherical harmonic transform indexing to produce high-angular-resolution EBSD (HR-EBSD) data. HR-EBSD data resolved the small misorientation angles of subgrain boundaries while imaging much larger data fields than possible with previously available techniques. The resulting data confirmed that steady-state flow stress is inversely proportional to the average subgrain size and that subgrain boundary misorientation angle increases with strain. The following new observations are reported. The rate of DGG increased with respect to time but decreased with respect to strain as strain rate increased. This behavior is rationalized through a simple model using separate rate parameters for the effects of time and strain. Subgrain size was not constant during steady-state deformation, but decreased slowly with increasing strain. Subgrain size distributions and subgrain boundary misorientation angle distributions were measured, and both remained approximately log-normal during steady-state deformation. Subgrain evolution demonstrated no dependence on parent grain size, crystallographic orientation, or Taylor factor. These new data suggest that steady-state flow stress is more likely controlled by the dislocation density internal to subgrains than by the spacing between subgrain boundaries.

dynamic grain growth↗

Review: Magnesium Sheet Alloy Development for Room Temperature Forming

Sheet metal forming operations in the automotive industry, including stamping, flanging, bending, hemming and trimming, are dominantly done at room temperature (RT). Unfortunately, the poor RT formability of magnesium due to its hexagonal close packed (HCP) structure and generally strong texture has limited the use of these processes in high-volume automotive production. However, the formability of magnesium can be improved via fine grain structure and random texture to enable some RT forming operations. Here, this paper presents the latest magnesium alloy development and evaluation by the United States Automotive Materials Partnership (USAMP) in collaboration with its university partners. A new sheet alloy developed in a recent USAMP project, ZAXME11100 (USAMP Alloy 2 Plus), offers excellent ductility (31% tensile elongation) and RT formability (7.8 mm Erichsen Index) in solution-treated condition (T4), and a high yield strength (270 MPa) upon post-forming aging treatment (T6), promising RT forming for automotive applications.

36 MATERIALS SCIENCE↗

ESM data downscaling: a comparison of super-resolution deep learning models

Abstract Climate projections at fine spatial resolutions are required to conduct accurate risk assessment for critical infrastructure and design adaptation planning. Generating these projections using advanced Earth system models (ESM) requires significant computational resources. To address this issue, various statistical downscaling techniques have been introduced to generate fine-resolution data from coarse-resolution simulations. In this study, we evaluate and compare five deep learning-based downscaling techniques, namely, super-resolution convolutional neural networks, fast super-resolution convolutional neural network ESM, efficient sub-pixel convolutional neural network, enhanced deep residual network (EDRN), and super-resolution generative adversarial network (SRGAN). These techniques are applied to a dataset generated by the Energy Exascale Earth System Model (E3SM), focusing on key surface variables such as surface temperature, shortwave heat flux, and longwave heat flux. Models are trained and validated using paired fine-resolution (0.25 $$^{\circ }$$ ∘ ) and coarse-resolution (1 $$^{\circ }$$ ∘ ) monthly data obtained from a 9-year simulation. Next, blind testing is performed using monthly data obtained from two different years outside of the training and validation set. To evaluate the efficiency of each technique, different statistical metrics are used, including mean squared error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and learned perceptual image patch similarity (LPIPS). The results show that EDRN outperforms other algorithms in terms of PSNR, SSIM, and MSE, but struggles to capture fine-scale features in the data. In contrast, SRGAN, a generative model that uses perceptual loss, excels in capturing fine details at boundaries and internal structures, resulting in lower LPIPS than other methods.

Pawar, Nikhil M. (ORCID:0000000211613289)↗

Evaluating indoor thermal resilience of passive and low-power cooling shelters for outdoor workers in India

India’s 231 million outdoor workers are exposed to deadly heat during heat waves. We report results from a simulation-based study that focuses on passive design of cooling shelters for the hot and dry climate zone of India. The goal is to design a cooler-than-outdoor shelter for outdoor workers’ intermittent rest and recovery from heat stress during their arduous outdoor work, to avoid heat-related morbidities and mortality. Expected indoor thermal conditions in low-cost cooling shelters deploying a range of passive designs and low-power active measures are investigated, consistent with the current Indian standards and practices, located in the city of Jodhpur in western India. Heat resilience of the shelter was measured with the predicted reduction of hazardous hours inside the shelter based on the wet-bulb globe temperature (WBGT) and extended heat index. These measures include improving the building envelope, installing cool roofs, using internal thermal mass, and natural ventilation. Additionally, a low-power active measure of using ventilation fans and ceiling fans is explored. EnergyPlus-based simulation results show that simple, commonly available measures, particularly natural ventilation and ceiling fans, achieve the most significant reductions in overheating danger hours, by 22% and 21%, respectively, while more complex or costly passive strategies yield only marginal additional benefits. Moreover, combined measure packages are identified that can reduce the indoor WBGT by 8 to 10 °C, eliminating overheating danger hours. These findings highlight the critical importance of scalable, low-cost, and easily deployable cooling solutions for developing resilient cooling shelters for vulnerable outdoor workers during heat waves in India.

building performance↗

Lifetime and Degradation Study of Poly(Methyl Methacrylate) via a Data-Driven Study Protocol Approach

We report to optimize and extend the service life of polymeric materials in outdoor environments, a domain knowledge-based and data-driven approach was utilized to quantitatively investigate the temporal evolution of degradation modes, mechanisms, and rates under various stepwise accelerated exposure conditions. Six formulations of poly(methyl methacrylate) (PMMA) with different combinations of stabilizing additives, including one unstabilized formulation, were exposed in three accelerated weathering conditions. Degradation was dependent on wavelength as samples in UV light at 340 nm (UVA) exposure showed the most yellowing. The unstabilized PMMA formulation showed much higher yellowness index values (59.5) than stabilized PMMA formulations (2–12). Urbach edge analysis shows a shift toward longer wavelength from 285 to 500 nm with increasing exposure time and an increased absorbance around 400 nm of visible region as the unstabilized samples increase in yellowing. The degradation mechanisms of PMMA were tracked using induced absorbance to dose at specific wavelengths that correspond to known degradation mechanisms. The degradation pathway of PMMA was modeled in a framework using network structural equation modeling (netSEM). netSEM showed changes in degradation pathway as PMMA transition stages of degradation.

36 MATERIALS SCIENCE↗

High-Speed X-Ray Stereo Digital Image Correlation in a Shock Tube

X-ray stereo digital image correlation (DIC) measurements were performed at 10 kHz on the internal surface of a jointed structure in a shock tube at a shock Mach number of 1.42 and compared with optical stereo DIC measurements on the outer, visible surface of the structure. The shock tube environment introduces temperature and density gradients in the gas through which the structure was imaged, resulting in spatial and temporal index of refraction variations. These variations cause bias errors in optical DIC measurements due to beam-steering but have minimal influence on x-ray DIC measurements. These results demonstrate the utility of time-resolved x-ray DIC measurements in complicated environments where optical measurements suffer severe errors and/or are precluded by lack of optical access.

42 ENGINEERING↗

Efficacy of Gadolinium Gallium Garnet (GGG) as a High-Impedance Optical Window for Shock Wave Experiments

We conducted a series of plate impact experiments to examine the efficacy of < 111>-oriented gadolinium gallium garnet (GGG) single crystals as high-impedance optical window for Photonic Doppler velocimetry (PDV) under shock and double-shock loading. At ~ 123 GPa, shocked GGG remains fully transparent to 1550 nm light for at least 250 ns without any signal degradation. Above 135 GPa, PDV data measured through GGG exhibit a gradual loss of fringe contrast following shock entrance, which eventually leads to transparency loss. The duration for which shocked GGG remains transparent decreases with increasing pressure, and at ~ 148 GPa, it becomes opaque within ~ 20–30 ns. This limits the use of GGG as an interferometry window between ~ 110–140 GPa under single shock loading. Within this pressure range, the refractive index of GGG increases linearly with density: n = 1.552 + 0.054ρ. In contrast to single shock loading, where GGG becomes opaque rapidly above ~ 140 GPa, double-shocked GGG remains optically transparent for over 100 ns when it is first shocked to ~ 123 GPa and then reshocked to significantly higher pressures (215–233 GPa). Our findings raise the exciting possibility of GGG being used as a high-impedance optical window in multi-shock and shock-ramp loading experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Three-dimensional atomic scale characterization of {11$\overline{2}$2} twin boundaries in titanium

The {11$\overline{2}$2}<11$\overline{23}$> compression twin can accommodate a considerable amount of strain under c-axis compression in Ti. However, unlike the tensile twin, the structure of the {10$\overline{1}$2}$\langle$$\overline{1}$011$\rangle$ compressive twins has not been completely characterized. In this study, we apply a combined technique of HR-TEM characterization, topological analysis, and atomistic simulations to explore the facets that bound the {11$\overline{2}$2}<11$\overline{23}$> twin in Ti. In addition to the currently known facets (CTB and B-Py), six new facets are observed and categorized for the first time from atomic-scale TEM observations along five crystallographic directions. The six new facets are (11$\overline{2}$0)//(11$\overline{2}$6), PrPr1, PyPy1, (2$\overline{11}$1)//($\overline{1}$2$\overline{1}$2), (1$\overline{1}$04)//(01$\overline{11}$), and (01$\overline{1}$0)//(2$\overline{11}$4). Results from the topological and computational analysis are in reasonable agreement with and support the HRTEM observations. Specifically, (1) the observed facets align with low-index interfaces in both twin and matrix domains, (2) the facets with lower surface energies are found to form extended interfaces, and (3) high-surface-energy facets are found at the twin tip region and explained by the fact that the energy of the combined facet and facet junction configuration is energetically preferred in the twin tip region. These results not only provide a comprehensive understanding of the 3D structure of the {11$\overline{2}$2}<11$\overline{23}$> compressive twins in Ti, but also validate the MD procedure and the Ti interatomic potential employed. This is extremely important for future study of the {11$\overline{2}$2} twin mobility and interactions with other defects, both features that remain extremely challenging to capture in experiments.

36 MATERIALS SCIENCE↗

An electronic origin to the oscillatory segregation behavior in Ni-Cr and other BCC defects in FCC metals

Ni-Cr alloys exhibit oscillatory segregation behaviors near low index surfaces, in which the preferred segregation species changes from Ni in the first layer to Cr in the second layer. In many dilute-alloy systems, this oscillatory pattern is attributed to the elastic release of stresses in the local lattice around the segregating solute or impurity atom. These stresses are mostly thought to originate from mismatches in the atomic size of the solute and host atoms. In Ni-Cr alloys, however, an appreciable mismatch in atomic size is not present, leading to questions about the origins of the oscillatory behavior in this alloy. Therefore, using density functional theory, we have modeled the segregation of a single Cr atom in the and surfaces of FCC Ni, an alloy which exhibits this oscillatory behavior. Using Bader charge analysis, we show that the negative energy correlates directly with the amount of charge on the Cr atom. As Ni atoms strip valence charge from the Cr, the Cr contracts slightly in size. The greatest contraction and highest positive charge for the Cr occurs when it is in the second layer of the surface where the system exhibits the oscillating negative segregation energy. We then find that this behavior persists in other alloy systems (Ag-Nb, Cu-Cr, Pt-Nb, and Pt-V), which exhibit similar atomic radii and electronegativity differences between host and solute to Ni-Cr. These represent alloys in which the host metal exhibits an FCC ground-state structure while the solute metal exhibits a BCC ground-state structure.

36 MATERIALS SCIENCE↗

Active and passive cooling approaches for a Southern California residential community

This study assesses cooling strategies in a low-income community in Southern California that lacks air conditioning and struggles with heat and air pollution. We used an urban building energy model and an electric distribution system model to evaluate active and passive cooling measures. The most effective space cooling measures were high-performance air-source heat pumps, cool coatings, window films, and harnessing the space cooling effect from heat pump water heaters. The results show that combining heat pump water heaters with window films and cool coatings reduces heat index hazard hours within buildings by 95 % to 99 % but increases total energy costs (equipment costs plus changes in utility bills) by 20 % to 60 % where the higher end includes building electrical upgrades. These measures also led to increased space heater use during colder months to avoid overcooling. Replacing conventional heaters with air source heat pumps eliminated unsafe indoor temperatures and reduced total energy use, but increased cost by 125 % to 150 %. In total, using heat pumps for space and water heating could reduce primary energy use by up to 57 %. The higher cost of active and passive cooling measures can be mitigated by existing and emerging incentive programs, especially those that support heat pumps. Electric distribution upgrades to support community electrification are estimated to increase utility costs by $\$$25 to $\$$40 per ratepayer per year. The results underscore the potential and challenges of adapting building infrastructure in communities at risk from climate and environmental stressors.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Understanding the influence of boron in additively manufactured GammaPrint®-700 CoNi-based superalloy

Boron is commonly added to superalloys in small amounts to enhance creep resistance, but can lead to cracking at high concentrations, especially during the additive manufacturing process. Two variants of CoNi-based GammaPrint®-700 superalloy with different B contents (0.08 at% vs 0.16 at%) were printed via laser powder bed fusion (LPBF) with the same printing parameters, with only the high B alloy exhibiting solidification cracking. Atom probe tomography (APT) revealed stronger segregation behaviors in the high B alloy compared to the low B alloy at both the inter-dendritic regions and grain boundaries (GBs). The segregation behavior at inter-dendritic regions was well captured with Scheil simulation and can correlate with the existing cracking susceptibility index (CSI) on cracking tendencies, although high angle GBs are where cracking occurs according to electron backscatter diffraction (EBSD) measurements. Additionally, the extent of GB segregation was compared between the high B and low B alloy. Higher B additions led to significantly more GB B segregation in the high B alloy compared to the low B alloy. Further, for the high B alloy, the cracked region of one GB exhibited higher levels of B compared to the uncracked region of the same GB. However, much higher B contents were also found in two other uncracked GBs in the high B alloy, which demonstrates that higher GB B concentrations are not fully responsible for the cracking. A much larger variance in GB B segregation content was found in the high B alloy compared to the low B alloy. These phenomena were explained with a solidification model with the GB segregation content expressed explicitly by a modified Langmuir-McLean equation. This model linked the GB segregation content with solidification undercooling, which can be used as quantitative cracking criteria for future builds.

36 MATERIALS SCIENCE↗

Aggregation in bottom-up vulnerability assessments and equity implications: The case of Jordanian households’ water supply

Bottom-up methods for water resources modeling rely on acceptability thresholds to find, through a response surface, which deeply uncertain futures lead to system failure. They commonly treat water users as aggregate actors, which may preclude analysis of the equity impacts of interventions. This paper explores how aggregation choices for large groups of water users lead to different policy recommendations in response surface assessments. Herein, two aggregation methods with varying parameters are considered: percentile satisfaction targets and generalized mean. A 2-dimensional stress-test assessment across groundwater availability and population is applied to household water supply in Jordan. The study compares six different policies covering supply enhancement and rebalancing, using a country-wide multi-agent model that characterizes households across socioeconomic strata. For different aggregation levels, policies are ordered by their associated robustness index. Results show that aggregation choices may modify response surfaces as much as policy changes and strongly determine policy preference. Modifying allocation rules can substantially reduce the disparity in household vulnerability. Preferences defined by aggregation intervals provide a finer understanding of trade-offs among water users and may improve deliberation over equity under deep uncertainty.

54 ENVIRONMENTAL SCIENCES↗

Quantifying carbon budget, crop yields and their responses to environmental variability using the ecosys model for U.S. Midwestern agroecosystems

As one of the major agricultural production areas in the world, the United States (U.S.) Midwest plays a vital role in the global food supply and agricultural ecosystem services. Although significant efforts have been made in modeling the carbon cycle dynamics over this area, large uncertainty still exists in the previous simulations in terms of reproducing individual components of the carbon cycle and their responses to environmental variability. Here we evaluated the performance of an advanced agroecosystem model, ecosys, in simulating carbon budgets over the U.S. Midwest, considering both the magnitude of carbon flux/yield and its response to environmental (climate and soil) variability. We conducted model simulations and evaluations at 7 cropland eddy-covariance sites as well as over 293 counties of Illinois, Indiana, and Iowa in the U.S. Midwest. The site-level simulations showed that ecosys captured both the magnitude and seasonal patterns of carbon fluxes (i.e., net ecosystem carbon exchange (NEE), ecosystem gross primary production (GPP), and ecosystem respiration (Reco)), leaf area index (LAI), and dynamic plant carbon allocation processes, with R2 equal to 0.92, 0.87, 0.87, and 0.78 for GPP, NEE, Reco, and LAI, respectively across all the sites compared with the observations. For regional scale simulations, ecosys reproduced the spatial distribution and interannual variability of corn and soybean yields with the constraints of observed yields and a new remotely sensed GPP product, with R2 of multi-year averaged simulated and observed yield equal 0.83 and 0.80 for corn and soybean, respectively. The simulated responses of carbon cycle dynamics to environmental variability were consistent with that from the empirical observations at both site and regional scales. Furthermore, our results demonstrated the applicability of ecosys in simulating the carbon cycle and soil carbon dynamics of the U.S. Midwestern agroecosystems under different climate and soil conditions.

54 ENVIRONMENTAL SCIENCES↗

Calibration approach and range of observed sap flow influences transpiration estimates from thermal dissipation sensors

Calibrating thermal dissipation (TD) sap flow sensors has become increasingly important to accurately estimate whole-tree transpiration, but it is unclear how the calibration approach itself influences the resulting coefficients and estimates. Here, we compare the two most common calibration approaches, gravimetric and potometric, using TD sensors inserted into Eucalyptus benthamii tree stems. The gravimetric approach uses an excised stem segment devoid of branches and leaves and pushes water through the stem using gravity, a positive force. The potometric approach uses a severed stem containing an intact canopy placed upright in a reservoir where water is pulled through the stem via transpiration, a negative force. We hypothesized that the positive pressure associated with gravimetric calibration would overestimate conductive sapwood area relative to that estimated from potometric calibration and that coefficients from these different approaches would result in different estimates of transpiration when applied to intact trees. We also predicted that calibrations could improve transpiration estimates by targeting the range of observed sap flow rates (i.e., K values) in intact trees. Conductive sapwood area was higher under gravimetric calibrations and resulting estimates of transpiration were lower compared to potometric calibrations. Segmented calibration curves, which fit two separate curves for the relationship between sap flux density (Fd) and sap flux index (K) based on the range of sap flow rates observed in intact trees, increased transpiration estimates from both gravimetric and potometric coefficients and diminished the magnitude of difference in transpiration estimates between approaches. Researchers should be aware that calibration approach and range of observed sap flow profoundly influences transpiration estimates from TD sensors and this likely applies to calibrations of other heat-based sap flow sensors.

54 ENVIRONMENTAL SCIENCES↗

Early season prediction of within-field crop yield variability by assimilating CubeSat data into a crop model

Accurate early season predictions of crop yield at the within-field scale can be used to address a range of crop production, management, and precision agricultural challenges. While the remote sensing of within-field insights has been a research goal for many years, it is only recently that observations with the required spatio-temporal resolutions, together with efficient assimilation methods to integrate these into modeling frameworks, have become available to advance yield prediction efforts. Here we explore a yield prediction approach that combines daily high-resolution CubeSat imagery with the APSIM crop model. The approach employs APSIM to train a linear regression that relates simulated yield to simulated leaf area index (LAI). That relationship is then used to identify the optimal regression date at which the LAI provides the best prediction of yield: in this case, approximately 14 weeks prior to harvest. Instead of applying the regression on satellite imagery that is coincident, or closest to, the regression date, our method implements a particle filter that integrates CubeSat-based LAI into APSIM to provide end-of-season high-resolution (3 m) yield maps weeks before the optimal regression date. The approach is demonstrated on a rainfed maize field located in Nebraska, USA, where suitable collections of both imagery and in-situ data were available for assessment. The procedure does not require in-field data to calibrate the regression model, with results showing that even with a single assimilation step, it is possible to provide yield estimates with good accuracy up to 21 days before the optimal regression date. Yield spatial variability was reproduced reasonably well, with a strong correlation to independently collected measurements (R 2 = 0.73 and rRMSE = 12%). When the field averaged yield was compared, our approach reduced yield prediction error from 1 Mg/ha (control case based on a calibrated APSIM model), to 0.5 Mg/ha (using satellite imagery alone), and then to 0.2 Mg/ha (results with assimilation up to three weeks prior to the optimal regression date). Such a capacity to provide spatially explicit yield predictions early in the season has considerable potential to enhance digital agricultural goals and improve end-of-season yield predictions.

54 ENVIRONMENTAL SCIENCES↗

Fine resolution remote sensing spectra improves estimates of gross primary production of croplands

Gross primary production (GPP) is a fundamental measure of the terrestrial carbon cycle critical to our understanding of ecosystem function under the changing climate and land use. Remote sensing enables access to continuous spatial coverage, but remains challenged in heterogeneous croplands. Coarse resolution products, like MOD17A (500 m), may aggregate fragmented land cover types commonly found in heavily managed landscapes and misrepresent their respective contribution to carbon production. Consequently, this study demonstrates the capability of fine-resolution imagery (20-30 m) and available red-edge vegetation indices to characterize GPP across seven Midwest cropping systems. Four sites were established on a 22-year-old USDA Conservation Reserve Program (CRP); and the other three on land conventionally farmed with corn-soybean-wheat rotation (AGR). We compare in situ GPP estimates from eddy-covariance towers with ten satellite models: eight variants of the vegetation photosynthesis models (VPM), of which five include a red-edge vegetation index, as well as conventional products Landsat CONUS GPP (30 m) and MOD17A2H V6 (500 m). Daily and cumulative fine-resolution imagery integrated within VPM generally agreed with tower-based GPP in heterogeneous landscapes more than those from MODIS 500 m VPM or conventional GPP products from MOD17AH V6 or Landsat 8 CONUS. Here, replacing EVI2 with red-edge indices NDRE2, NDRE1, and MTCI in Sentinel 2 VPMs notably improved explanation of variance and estimation of cumulative GPP. While existing methods using MODIS- and Landsat-derived GPP are important baselines for regional and global studies, future research may benefit from the higher spatial, temporal, and radiometric resolution.

54 ENVIRONMENTAL SCIENCES↗

Energy and power quality measurement for electrical distribution in AC and DC microgrid buildings

Today's selection of DC microgrid buildings features a diverse set of electrical topologies and turnkey solutions, each with specific design trade-offs and optimizations. Designers desperately need standardized metrics and procedures for measurement and verification (M&V) to analyze and compare the advantages of each DC solution to traditional AC building networks. This work develops M&V procedures for quantifying and comparing the energy efficiency and power quality in buildings. To calculate full-building efficiency, this work introduces the measurement-informed modeling method, a procedure that develops and refines a building's energy model with metered data. To quantify power quality, this work defines a new voltage quality index that applies to both AC and DC buildings. This article describes the equipment, instrumentation, and operation necessary to calculate the efficiency and power quality. It then demonstrates these methods with a set of field tests. We report these M&V procedures can ultimately be used to compare and improve the efficiency and power quality of various DC topologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗