Search NASA⌕ Search

SEARCH · Search NASA

Results for “Selection optimization”

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 883 records · Page 49

N 2 O Formation Mechanism and Suppression Strategy on Pt Catalysts for NO x Removal from Hydrogen-Internal Combustion Engines

Pt-based catalysts exhibit excellent low-temperature activity in the selective catalytic reduction of NO x with H 2 (H 2 -SCR), but their tendency to form N 2 O poses a significant challenge for practical use. This issue is further complicated by unclear formation mechanisms, hindering the development of more efficient catalysts. This study explored the N 2 O generation mechanisms on Pt catalysts supported by MgO, Al 2 O 3 , SiO 2 , and TiO 2 , aiming to achieve a deep understanding that could advance the Pt catalysts with high NO x conversion and minimized N 2 O emissions. Through systematic kinetics and characterization analyses, the direct influence of the support acidity and reactant dynamics (O 2 and NO) on N 2 O formation was clearly revealed. Notably, the Pt catalysts with strong NO adsorption capacity showed reduced N 2 O generation, highlighting the critical role of NO adsorption sites in the H 2 -SCR process. By incorporation of NO adsorption sites (i.e., MgO, BaO, CeO 2 ) onto Pt/SiO 2 , both the H 2 -SCR efficiency and N 2 selectivity (reduced N 2 O selectivity) were significantly enhanced, effectively reducing the N 2 O emissions through optimized surface NO adsorption. These findings provide a design framework for more selective Pt-based catalysts, advancing H 2 -SCR systems for effective NO x abatement from hydrogen-internal combustion engines, which is a promising carbon-free transportation technology.

36 MATERIALS SCIENCE↗

Scientific frontiers of agrivoltaic cropping systems

Agrivoltaic (AV) systems integrate agriculture with electricity conversion through photovoltaic (PV) modules. Compared with conventional ground-mounted PV systems, AV systems can reduce land-use competition and offer agronomic and economic advantages, such as more stable crop production and additional farm income. However, AV systems can decrease agricultural performance and are typically 20-90% costlier to install than conventional PV systems. Here, in this Review, we analyse the implementation of AV cropping systems to preserve agricultural activities and highlight challenges and barriers. The global electricity potential of AV systems is ~66-385 PWh annually, depending on PV technology and installation density, if deployed in the most suitable areas, without accounting for grid availability. Scaling up has been hindered by crop selection for shading conditions, decreased energy conversion per unit of land area and issues with social acceptance, landscape impact and environmental sustainability. These issues can be addressed by developments such as wavelength-selective PV; system configurations, such as optimizing module spacing to reduce shading; and operational methods, such as optimizing tracking strategies and integrating agricultural infrastructure. Cross-sector policies can support AV systems by addressing the needs of diverse stakeholders over shared land resources. Further development will require collaboration among the design, performance, deployment and systems research communities.

14 SOLAR ENERGY↗

Beyond single crystals: Imaging rubrene polymorphism across crystalline batches through lattice phonon Raman microscopy

Polymorphism is an issue troubling numerous scientific fields. A phenomenon where molecules can arrange in different orientations in a crystal lattice, polymorphism in the field of organic photovoltaic materials can dramatically change electronic properties of these materials. Rubrene is a benchmark photovoltaic material showing high carrier mobility in only one of its three polymorphs. To use rubrene in devices, it is important to quantify the polymorph distribution arising from a particular crystal growth method. However, current methods for characterizing polymorphism are either destructive or inefficient for batch scale characterization. Lattice phonon Raman spectroscopy has the ability to distinguish between polymorphs based on low frequency intermolecular vibrations. Here, we present here the addition of microscopy to lattice phonon Raman spectroscopy, which allows us to not only characterize polymorphs efficiently and nondestructively through Raman spectroscopy but also concurrently gain information on the size and morphology of the polymorphs. We provide examples for how this technique can be used to perform large, batch scale polymorph characterization for crystals grown from solution and physical vapor transport.We end with a case study showing how Raman microscopy can be used to efficiently optimize a green crystal growth method, selecting for large orthorhombic crystals desired for rubrene electronic device applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Inverse design of pore wall chemistry and topology through active learning of surface group interactions

Design of next-generation membranes requires a nanoscopic understanding of the effect of biologically inspired heterogeneous surface chemistries and topologies (roughness) on local water and solute behavior. In particular, the rejection of small, neutral solutes, such as boric acid, poses a heretofore unsolved challenge. In prior work, a computational inverse design technique using an evolutionary optimization successfully uncovered new surface design strategies for optimized transport of water over solutes in smooth, model pores consisting of two surface chemistries. However, extending such an approach to more complex (and realistic) scenarios involving many surface chemistries as well as surface roughness is challenging due to the expanded design space. In this work, we develop a new approach that uses active learning to optimize in a reduced feature space of surface group interactions, finding parameters that lead to their assembly into ordered, optimal patterns. This approach rapidly identifies novel surface functionalizations that maximize the difference in water and boric acid transport through the nanopore. Moreover, we find that the roughness of the nanopore wall, independent of its chemistry, can be leveraged to enhance transport selectivity: oscillations in the pore wall diameter optimally inhibit boric acid transport by creating energetic wells from which the solute must escape to transport down the pore. Furthermore, this proof-of-concept demonstrates the potential for active learning strategies, in concert with molecular simulations, to rapidly navigate complex design spaces of aqueous interfaces and is promising as a tool for engineering water-mediated surface interactions for a broad range of applications.

36 MATERIALS SCIENCE↗

Design of an epithermal neutron velocity selection system for the Penn State Breazeale Reactor

A series of mechanical neutron choppers to operate as a velocity selection system have been developed for the Pennsylvania State Breazeal Reactor (PSBR). This chopper system will provide pulsed epithermal neutrons in the energy range of 0.5–40 eV with 2% or better energy resolution, and with a transmission of 1E-6 or better. Four different chopper geometries have been evaluated for their utility as mechanical neutron choppers. Specifically, Fermi, ring, piston, and disc choppers have been evaluated to assess their potential neutronics performance and mechanical constructability. A series of high-speed disc choppers were selected for the final design, and optimization work was performed to maximize the neutron pulse intensity. It is estimated that the optimized system will produce an epithermal neutron intensity of approximately 96 n/s. This system can also be operated in a time of flight (TOF) configuration such that the neutrons arriving at the source have a white spectrum. This operation can be accomplished by leaving the second stage of choppers in the open position, or by removing it from the beam completely. Such unique source of epithermal neutrons produced by this chopper system will have applications in both prompt and delayed epithermal neutron activation analysis (ENAA), as well as in neutron resonance transmission analysis (NRTA).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Genomic prediction of hybrid performance for agronomic traits in sorghum

Hybrid breeding in sorghum [Sorghum bicolor (L.) Moench] utilizes the cytoplasmic-nuclear male sterility (CMS) system for seed production and subsequently harnesses heterosis. Since the cost of developing and evaluating inbred and hybrid lines in the CMS system is costly and time-consuming, genomic prediction of parental lines and hybrids is based on genetic data genotype. We generated 602 hybrids by crossing two female (A) lines with 301 diverse and elite male (R) lines from the sorghum association panel and collected phenotypic data for agronomic traits over two years. We genotyped the inbred parents using whole genome resequencing and used 2,687,342 high quality (minor allele frequency > 2%) single nucleotide polymorphisms for genomic prediction. For grain yield, the experimental hybrids exhibited an average mid-parent heterosis of 40%. Genomic best linear unbiased prediction (GBLUP) for hybrid performance yielded an average prediction accuracy of 0.76–0.93 under the prediction scenario where both parental lines in validation sets were included in the training sets (T2). However, when only female tester was shared between training and validation sets (T1F), prediction accuracies declined by 12–90%, with plant height showing the greatest decline. Mean accuracies for predicting the general combining ability of male parents ranged from 0.33 to 0.62 for all traits. Our results showed hybrid performance for agronomic traits can be predicted with high accuracy, and optimizing genomic relationship is essential for optimal training population design for genomic selection in sorghum breeding.

60 APPLIED LIFE SCIENCES↗

Prolonging genetic circuit stability through adaptive evolution of overlapping genes

Abstract The development of synthetic biological circuits that maintain functionality over application-relevant time scales remains a significant challenge. Here, we employed synthetic overlapping sequences in which one gene is encoded or ‘entangled’ entirely within an alternative reading frame of another gene. In this design, the toxin-encoding relE was entangled within ilvA, which encodes threonine deaminase, an enzyme essential for isoleucine biosynthesis. A functional entanglement construct was obtained upon modification of the ribosome-binding site of the internal relE gene. Using this optimized design, we found that the selection pressure to maintain functional IlvA stabilized the production of burdensome RelE for >130 generations, which compares favorably with the most stable kill-switch circuits developed to date. This stabilizing effect was achieved through a complete alteration of the allowable landscape of mutations such that mutations inactivating the entangled genes were disfavored. Instead, the majority of lineages accumulated mutations within the regulatory region of ilvA. By reducing baseline relE expression, these more ‘benign’ mutations lowered circuit burden, which suppressed the accumulation of relE-inactivating mutations, thereby prolonging kill-switch function. Overall, this work demonstrates the utility of sequence entanglement paired with an adaptive laboratory evolution campaign to increase the evolutionary stability of burdensome synthetic circuits.

59 BASIC BIOLOGICAL SCIENCES↗

Search for an exotic S = – 2 , Q = – 2 baryon resonance in proton-proton interactions at s N N = 17.3 GeV

Pentaquark states have been extensively investigated theoretically in the context of the constituent quark model. In this paper results of an experimental search for pentaquarks in the Ξ – π – , Ξ – π + , Ξ ¯ + π – and Ξ ¯ + π + invariant mass spectra in proton-proton interactions at s = 17.3 GeV are presented. Previous possible evidence from the NA49 collaboration of the existence of a narrow Ξ – π – baryon resonance in p + p interactions is not confirmed with almost 10 times greater event statistics. The search was performed using the NA61/SHINE detector which reuses the main components of the NA49 apparatus. No signal was observed with either the selection cuts of NA49 or newly optimized cuts.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Net Zero Energy Model for Wastewater Treatment Plants

The primary objective of this study is to achieve net-zero energy (NZE) wastewater treatment plants (WWTPs) by utilizing energy efficiency opportunities (EEO), combined heat and power (CHP) systems, and other renewable energy (RE) sources, e.g., solar, water, and wind powers. Herein, this study discusses an innovative energy solution for WWTPs in the United States, and one of the WWTPs with a flow capacity of 1.5 million gallons per day (MGD) was selected as a case study. An optimization tool, Hybrid Optimization of Multiple Energy Resources (HOMER) software, is used in this study to find the best energy system configuration to run the system. An energy audit for one WWTP was conducted in early 2020 and the report is used to do this study. The proposed EEOs were able to reduce WWTP energy consumption by about 11%. The excess anaerobic digester gas was utilized in a CHP system to cover about 42% of the facility’s consumption. Also, 3% of the utility energy consumption can be claimed by microturbines in the aeration tanks. Another two renewable energy systems, solar photovoltaic (PV) with 29% and water turbines with 15%, contribute to covering 100% of the WWTP energy consumption and achieving an NZE WWTP.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Epstein-Barr Virus Epitope–Major Histocompatibility Complex Interaction Combined with Convergent Recombination Drives Selection of Diverse T Cell Receptor α and β Repertoires

Recognition modes of individual T cell receptors (TCRs) are well studied, but factors driving the selection of TCR repertoires from primary through persistent human virus infections are less well understood. Using deep sequencing, we demonstrate a high degree of diversity of Epstein-Barr virus (EBV)-specific clonotypes in acute infectious mononucleosis (AIM). Only 9% of unique clonotypes detected in AIM persisted into convalescence; the majority (91%) of unique clonotypes detected in AIM were not detected in convalescence and were seeming replaced by equally diverse “de novo” clonotypes. The persistent clonotypes had a greater probability of being generated than nonpersistent clonotypes due to convergence recombination of multiple nucleotide sequences to encode the same amino acid sequence, as well as the use of shorter complementarity-determining regions 3 (CDR3s) with fewer nucleotide additions (i.e., sequences closer to germ line). Moreover, the two most immunodominant HLA-A2-restricted EBV epitopes, BRLF1 109 and BMLF1 280 , show highly distinct antigen-specific public (i.e., shared between individuals) features. In fact, TCRα CDR3 motifs played a dominant role, while TCRβ played a minimal role, in the selection of TCR repertoire to an immunodominant EBV epitope, BRLF1. This contrasts with the majority of previously reported repertoires, which appear to be selected either on TCRβ CDR3 interactions with peptide/major histocompatibility complex (MHC) or in combination with TCRα CDR3. Understanding of how TCR-peptide-MHC complex interactions drive repertoire selection can be used to develop optimal strategies for vaccine design or generation of appropriate adoptive immunotherapies for viral infections in transplant settings or for cancer.

59 BASIC BIOLOGICAL SCIENCES↗

xesn: Echo state networks powered by Xarray and Dask

Xesn is a Python package that allows scientists to easily design Echo State Networks (ESNs) for forecasting problems. ESNs are a Recurrent Neural Network architecture introduced by Jaeger (2001) that are part of a class of techniques termed Reservoir Computing. One defining characteristic of these techniques is that all internal weights are determined by a handful of global, scalar parameters, thereby avoiding problems during backpropagation and reducing training time significantly. Because this architecture is conceptually simple, many scientists implement ESNs from scratch, leading to questions about computational performance. Xesn offers a straightforward, standard implementation of ESNs that operates efficiently on CPU and GPU hardware. The package leverages optimization tools to automate the parameter selection process, so that scientists can reduce the time finding a good architecture and focus on using ESNs for their domain application. Importantly, the package flexibly handles forecasting tasks for out-of-core, multi-dimensional datasets, eliminating the need to write parallel programming code. Xesn was initially developed to handle the problem of forecasting weather dynamics, and so it integrates naturally with Python packages that have become familiar to weather and climate scientists such as Xarray (Hoyer & Hamman, 2017). However, the software is ultimately general enough to be utilized in other domains where ESNs have been useful, such as in signal processing (Jaeger & Haas, 2004).

97 MATHEMATICS AND COMPUTING↗

Novel Carbon (C)-Boron (B)-Nitrogen (N)-Containing H2 Storage Materials

The following summarizes the research conducted for DOE project DE-EE0005658 “Novel Carbon(C)-Boron(B)-Nitrogen(N)-Containing H2 Storage Materials”. This work focused in part on the continued study of two materials identified from the preceding project DE-FG360GO18143 (“Hydrogen Storage by Novel CBN Heterocycle Materials”) as lead candidates to meet the DOE technical targets for either vehicular or non-automotive hydrogen storage applications. Specifically, a room-temperature liquid, 3-methyl-1,2-cyclopentane (B), and a high H2 capacity solid, 1,2-BN-cyclohexane (J), were selected for further characterization and performance optimization. In addition to these compounds, the current project also aimed to prepare several new materials predicted to be disposed towards direct reversibility of H2 release and uptake, a feature deemed critical to achieving efficient recycling of spent fuel end products. To assist in the rational design of these and other next-generation materials, this project undertook to investigate the mechanism of hydrogen release from established compounds (mainly B and J) using a combined experimental/computational approach. Among this project’s signature accomplishments, the preliminary synthetic route to B was optimized for production on decagram scale. With such quantities of material available, its performance in powering an actual 30 W proton exchange membrane (PEM) fuel cell stack was tested and found to be identical to that of facility H2. Despite this positive proof-of-concept achievement, however, further consideration of neat B as a potential hydrogen storage material was abandoned due to evidence of thermal instability. Specifically, mass spectrometry-coupled thermogravimetric analysis (TGA-MS) revealed significant H2 release from B to initiate at 50 °C, well below the 60 °C minimum threshold set by the DOE. This result prompted a more extensive investigation in the decomposition mechanism of B vis-à-vis that of J, which exhibited in neat form a substantially higher onset temperature for spontaneous H2 release (70 °C). Solution-phase kinetic experiments using ReactIR established a second-order dependence for the initial loss of H2 from both B and J; Arrhenius analysis, however, revealed the activation barrier for this reaction was lower for B than for J, which presumably contributes to the diminished thermal stability of the former. On the basis of these and other experimental results, extensive computational efforts yielded a reasonable mechanistic model for the dehydrogenation of 1,2-BN-cycloalkane materials. While the prospect of neat B as a suitable hydrogen storage material was discarded, it was proposed that the combination of B with more thermally stable amine-borane-based materials might afford mixtures with improved properties. Indeed, when B was combined with ammonia borane (AB) in a 2:1 molar ratio, the two materials formed a liquid. More significantly, this mixture remained liquid even after complete dehydrogenation, thus establishing the potential for a single-phase fuel cycle. (In contrast, the dehydrogenation product of neat B is a low melting solid (mp = 28-30 °C).) Another advantage conferred by the blend formulation was a dramatic reduction in the amount of borazine produced by AB. Borazine is a well-known contaminant of H2 produced by the thermal decomposition of neat AB, and exerts deleterious effects on fuel cell performance. Residual gas analysis (RGA) of the gas stream generated from the B-AB blend, however, detected just 0.01% borazine content when a Pt-Ni nanoparticle dehydrogenation catalyst was used. In all ii then, the 2:1 B-AB blend marks a major achievement in the effort to develop a suitable liquid amine-borane hydrogen storage material, and merits further investigation into the optimization for practical adoption. Similar realization of the potential of J as a high % wt. H2 material required a method to dehydrogenate the carbonaceous components of the molecule without the use of a sacrificial hydrogen acceptor, as had been reported in the previous project. Ultimately, this reaction was achieved for a B,N-disubstituted BN-cyclohexene model substrate using a gas flow system with a fixed Pd/C catalyst bed. Considerable work remains, however, to translate these initial results into a general protocol for complete dehydrogenation of fully saturated BN-cycloalkane materials such as J. With concrete confirmation of the possibility to perform both BN and CC dehydrogenation on a single theoretical substrate, COMSOL modeling was used to evaluate the effects of thermodynamically coupling the two reactions. It was hypothesized that the heat generated from exothermic BN dehydrogenation would partially drive the endothermic CC dehydrogenation reaction; this additional heat consumption was expected to in turn confer the benefit of lowering the maximum reactor temperature. A two-dimensional model of an axisymmetric reactor including experimental kinetic and calculated thermodynamic parameters for both reactions did indeed predict these outcomes. The extent to which the effects of thermodynamic coupling actually manifested, however, were also revealed to depend strongly on the relative rates of the two reactions, as well as the magnitude of the equilibrium constant governing the progress of the endothermic process. Given the evident complexity of attaining high effective % wt. H2 capacity with J, alternative systems were investigated for greater facility of extensive H2 release. Among those studied, 1,2,4,5-bis-BN-cyclohexane (H) demonstrated the most favorable properties, particularly with respect to thermal stability: rather than decompose, a neat sample instead sublimed when heated above 150 °C. Nevertheless, two commercially available catalytic systems were identified to effect release of two H2 equivalents from H. Release of further equivalents were apparently impeded by the formation of either polymeric material or one of two dimeric cage compounds depending on the catalyst used. Notably, a method to regenerate H from these product mixtures remains to be developed. Thus, while H may prove useful for certain long-term energy storage needs, it is currently less suited applications involving frequent fuel consumption. Similar difficulties were also encountered in attempts to realize the complete fuel cycle of 1,3-BN-cyclohexane (E) and B,N-substituted derivatives thereof. It had been initially proposed that E would provide for readily reversible BN dehydrogenation through a measure of frustrated Lewis pair-type character. Indeed, computations predicted this reaction would be essentially thermoneutral in solution. In the course of attempts to fully hydrogenate the spent fuel, however, dimeric species formed and proved resistant to further BN reduction. While a number of monomeric cyclic compounds were also successfully synthesized as formal boron-nitrogen frustrated Lewis pairs, none demonstrated any capacity to split H2 across the BN unit. The challenge of developing a practical amine-borane-based material for readily reversible hydrogen storage thus remains unresolved at this time. As such, it deserves consideration as a major objective of any future work.

08 HYDROGEN↗

Overhead longwave infrared hyperspectral material identification using radiometric models

Material detection algorithms used in hyperspectral data processing are computationally efficient but can produce relatively high numbers of false positives. Material identification performed as a secondary processing step on detected pixels can help separate true and false positives. This paper presents a material identification processing chain for longwave infrared hyperspectral data of solid materials collected from airborne platforms. The algorithms utilize unwhitened radiance data and an iterative algorithm that determines the temperature, humidity, and ozone of the atmospheric profile. Pixel unmixing is done using constrained linear regression and Bayesian Information Criteria for model selection. The resulting product includes an optimal atmospheric profile and full radiance material model that includes material temperature, abundance values, and several fit statistics. A logistic regression method utilizing all model parameters to improve identification is also presented. This paper details the processing chain and provides justification for the algorithms used. Several examples are provided using modeled data at different noise levels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Origins of Matter on Near-Exascale Supercomputing

This LDRD addressed one of the central questions in physics today: the lack of antimatter relative to matter in the universe. If antimatter and matter existed in equal amounts they would have annihilated into radiation and we would not exist today. DOE is funding experiments to investigate processes that could lead to lepton number violation and the resulting neutrino-less double beta decay (0nbb) signal that may be observed (lepton number is a property of elementary particles similar to electric charge and lepton number violation would explain the matter-antimatter imbalance). However, even if the 0nbb decay is detected in these experiments, the physics mechanism that violates lepton number would not be known, as there are several candidates. Determining the appropriate mechanism from the experimental data requires theoretical calculations. Theoretical effort in the field has focused on long-range 0nbb decay mechanisms associated with the exchange of light neutrinos between two nucleons. An equally important set of mechanisms are associated with the exchange of heavy particles and short-range physics, including the exchange of massive Majorana neutrinos. Calculating the event rate for 0nbb decays for candidate theories involving heavy particle exchange requires large-scale Lattice simulations of the underlying fundamental theory of Quantum Chromodynamics (QCD). We have performed these simulations on the LLNL supercomputers and have calculated the necessary matrix elements of short-range operators that arise from the exchange of heavy mediators that contribute to 0nbb decay via the leading pion exchange diagrams. Our published results can now be used as input to effective field theory calculations to calculate the 0nbb decay rate for the nuclei involved in the various experimental detectors. In the process of this work we entered the 2018 Gordon Bell Prize competition (the highest prize in scientific supercomputing) with our innovative and highly optimized code and methods and were selected as one of the six international finalists. During this effort we helped with the bring-up of the new LLNL Sierra and Lassen supercomputers by identifying hardware and software problems. Aiming towards the next step of this research, involving the sub-leading nucleon-nucleon direct vertex, we have developed algorithms and codes that will play a significant role in future Lattice QCD calculations involving nucleon-nucleon interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Feature Based Qualification of 17-4PH Stainless Steel to Evaluate Location-Specific Variability in Wire Arc Additive Manufacturing

Qualifying large-scale metal additive manufacturing (M-AM) technologies such as wire arc additive manufacturing (WAAM) can be challenging. This is especially significant in precipitation hardened martensitic stainless steels like SS 17-4PH, where thermal histories induce location-specific microstructural variability and property anisotropy. The Department of Defense (DOD) and the United States Army Combat Capabilities Development Command Ground Vehicle Systems Center (GVSC) Ground Vehicle Materials Engineering (GVME) aim to build robust and qualified large-scale M-AM workflows that could reduce the time and cost through quick and informed evaluation, testing, and development of feedstock, processes, and parts. The report presents the findings from the collaborative efforts between Oak Ridge National Laboratory (ORNL) and the U.S. Army GVSC GVME. The aim of this project was to develop a geometric feature-based qualification framework for WAAM of SS 17-4PH components. This report outlines selection methodology of representative build geometries, optimization of WAAM process parameters, in-situ monitoring, microstructure-property evaluation, thermal simulations, as well as data visualization techniques incorporated in this project. The results from this project demonstrate a clear understanding of thermal history dependent phase evolution and consequent location-specific property variations in WAAM of SS 17-4PH. These results in conjunction with the data-driven methodologies used in this project are expected to reduce qualification timelines, improve predictability, and accelerate the development of reliable feature-based qualification strategies for part production via large-scale M-AM technologies.

36 MATERIALS SCIENCE↗

Agrivoltaics: Unlocking the Potential of Dual Land Use

This tutorial will delve into the practical and technical considerations for agrivoltaic systems, including crop selection, agricultural practices, and solar energy optimization. Leveraging insights from successful case studies, we'll address challenges such as policy barriers and regulatory gaps while exploring opportunities and incentives for implementation. With a focus on PV expertise, attendees will gain actionable knowledge on designing and evaluating dual-use systems that balance energy generation with agricultural productivity.

14 SOLAR ENERGY↗

Sensitivity of Riparian Buffer Designs to Climate Change—Nutrient and Sediment Loading to Streams: A Case Study in the Albemarle-Pamlico River Basins (USA) Using HAWQS

Riparian buffer zones (RBZs) provide multiple benefits to watershed ecosystems. We aimed to conduct an extensive sensitivity analysis of the RBZ designs to climate change nutrient and sediment loadings to streams. We designed 135 simulation scenarios starting with the six baselines RBZs (grass, urban, two-zone forest, three-zone forest, wildlife, and naturalized) in three 12-digit Hydrologic Unit Code watersheds within the Albemarle-Pamlico river basin (USA). Using the hydrologic and water quality system (HAWQS), we assessed the sensitivity of the designs to five water quality indicator (WQI) parameters: dissolved oxygen (DO), total phosphorous (TP), total nitrogen (TN), sediment (SD), and biochemical oxygen demand (BD). To understand the climate mitigation potential of RBZs, we identified a subset of future climate change projection models of air temperature and precipitation using EPA’s Locating and Selecting Scenarios Online tool. Analyses revealed optimal RBZ designs for the three watersheds. In terms of watershed ecosystem services sustainability, the optimal Urban RBZ in contemporary climate (1983–2018) reduced SD from 61–96%, TN from 34–55%, TP from 9–48%, and BD from 53–99%, and raised DO from 4–10% with respect to No-RBZ in the three watersheds. The late century’s (2070–2099) extreme mean annual climate changes significantly increased the projected SD and BD; however, the addition of urban RBZs was projected to offset the climate change reducing SD from 28–94% and BD from 69–93% in the watersheds. All other types of RBZs are also projected to fully mitigate the climate change impacts on WQI parameters except three-zone RBZ.

54 ENVIRONMENTAL SCIENCES↗