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At least 1,063 records · Page 59

Electric vehicle supply equipment location and capacity allocation for fixed-route networks

Electric vehicle (EV) supply equipment location and allocation (EVSELCA) problems for freight vehicles are becoming more important because of the trending electrification shift. Some previous works address EV charger location and vehicle routing problems simultaneously by generating vehicle routes from scratch. Although such routes can be efficient, introducing new routes may violate practical constraints, such as drive schedules, and satisfying electrification requirements can require dramatically altering existing routes. To address the challenges in the prevailing adoption scheme, we approach the problem from a fixed -route perspective. We develop a mixed -integer linear program, a clustering approach, and a metaheuristic solution method using a genetic algorithm (GA) to solve the EVSELCA problem. The clustering approach simplifies the problem by grouping customers into clusters, while the GA generates solutions that are shown to be nearly optimal for small problem cases. A case study examines how charger costs, energy costs, the value of time (VOT), and battery capacity impact the cost of the EVSELCA. Charger equipment costs were found to be the most significant component in the objective function, leading to a substantial reduction in cost when decreased. VOT costs exhibited a significant decrease with rising energy costs. Further, an increase in VOT resulted in a notable rise in the number of fast chargers. Longer EV ranges decrease total costs up to a certain point, beyond which the decrease in total costs is negligible.

33 ADVANCED PROPULSION SYSTEMS↗

Poster — Thur Eve — 35: The impact of intensity- and energy-modulated photon radiotherapy (XMRT) optimization on a variety of organ geometries

We previously reported on a novel, modulated in both energy and intensity; photon radiotherapy (XMRT) optimization technique. The purpose of this investigation was to test this XMRT optimization against conventional intensity modulated radiotherapy (IMRT) optimization on four different organ test geometries. All geometries mimicked clinically relevant scenarios. Both IMRT and XMRT were based on a linear programming approach where the objective function was the mean dose to healthy organs and organ-specific linear dose-point constraints were used. For IMRT, the beam energy was fixed to 6 MV while XMRT optimized in terms of both 6 and 18 MV beams. All plans consisted of a seven beam coplanar arrangement. All organ geometries were contoured on a 25cm diameter cylindrical water phantom in open source radiotherapy research software known as CERR. Solutions for both IMRT and XMRT were obtained for each geometry using a numerical solver Gurobi. Analyzing the quality of the solutions was done by comparing dose distributions and dose volume histograms calculated using CERR. For all four geometries, IMRT and XMRT solutions were comparable in terms of target coverage. For two of the geometries, IMRT provided an advantage in terms of reduced dose to the healthy structures. XMRT showed improved dose reduction to healthy organs for one geometry and a comparable dose distribution to IMRT for the remaining geometry. The inability to exploit the benefits of using multiple energies may be attributed to limited water phantom diameter and having the majority of the organs in close proximity to the transverse axis.

60 APPLIED LIFE SCIENCES↗

Space Launch System Accelerated Booster Development Cycle

With the retirement of the Space Shuttle, NASA is seeking to reinvigorate the national space program and recapture the public s interest in human space exploration by developing missions to the Moon, near-earth asteroids, Lagrange points, Mars, and beyond. The would-be successor to the Space Shuttle, NASA s Constellation Program, planned to take humans back to the Moon by 2020, but due to budgetary constraints was cancelled in 2010 in search of a more "affordable, sustainable, and realistic" concept2. Following a number of studies, the much anticipated Space Launch System (SLS) was unveiled in September of 2011. The SLS core architecture consists of a cryogenic first stage with five Space Shuttle Main Engines (SSMEs), and a cryogenic second stage using a new J-2X engine3. The baseline configuration employs two 5-segment solid rocket boosters to achieve a 70 metric ton payload capability, but a new, more capable booster system will be required to attain the goal of 130 metric tons to orbit. To this end, NASA s Marshall Space Flight Center recently released a NASA Research Announcement (NRA) entitled "Space Launch System (SLS) Advanced Booster Engineering Demonstration and/or Risk Reduction." The increased emphasis on affordability is evident in the language used in the NRA, which is focused on risk reduction "leading to an affordable Advanced Booster that meets the evolved capabilities of SLS" and "enabling competition" to "enhance SLS affordability. The purpose of the work presented in this paper is to perform an independent assessment of the elements that make up an affordable and realistic path forward for the SLS booster system, utilizing advanced design methods and technology evaluation techniques. The goal is to identify elements that will enable a more sustainable development program by exploring the trade space of heavy lift booster systems and focusing on affordability, operability, and reliability at the system and subsystem levels5. For this study, affordability is defined as lifecycle cost, which includes design, development, test, and engineering (DDT&E), production and operational costs (P&O). For this study, the system objectives include reducing DDT&E schedule by a factor of three, showing 99.9% reliability, flying up to four times per year, serving both crew and cargo missions, and evolving to a lift capability of 130 metric tons.3 After identifying gaps in the current system s capabilities, this study seeks to identify non-traditional and innovative technologies and processes that may improve performance in these areas and assess their impacts on booster system development. The DDT&E phase may be improved by incorporating incremental development testing and integrated demonstrations to mitigate risk. To further reduce DDT&E, this study will also consider how aspects of the booster system may have commonality with other users, such as the Department of Defense, commercial applications, or international partners; by sharing some of the risk and investment, the overall development cost may be reduced. Consideration is not limited to solid and liquid rocket boosters. A set of functional performance characteristics, such as engine thrust, specific impulse (Isp), mixture ratio, and throttle range are identified and their impacts on the system are evaluated. This study also identifies how such characteristics affect overall life cycle cost, including DDT&E and fixed and variable P&O.

Arockiam, Nicole↗

What can we learn from N 2 O isotope data? – Analytics, processes and modelling

The isotopic composition of nitrous oxide (N 2 O) provides useful information for evaluating N 2 O sources and budgets. Due to the co–occurrence of multiple N 2 O transformation pathways, it is, however, challenging to use isotopic information to quantify the contribution of distinct processes across variable spatiotemporal scales. Here, we present an overview of recent progress in N 2 O isotopic studies and provide suggestions for future research, mainly focusing on: analytical techniques; production and consumption processes; and interpretation and modelling approaches. Comparing isotope–ratio mass spectrometry (IRMS) with laser absorption spectroscopy (LAS), we conclude that IRMS is a precise technique for laboratory analysis of N 2 O isotopes, while LAS is more suitable for in situ/inline studies and offers advantages for site–specific analyses. When reviewing the link between the N 2 O isotopic composition and underlying mechanisms/processes, we find that, at the molecular scale, the specific enzymes and mechanisms involved determine isotopic fractionation effects. In contrast, at plot–to–global scales, mixing of N 2 O derived from different processes and their isotopic variability must be considered. We also find that dual isotope plots are effective for semi–quantitative attribution of co–occurring N 2 O production and reduction processes. More recently, process–based N 2 O isotopic models have been developed for natural abundance and 15 N–tracing studies, and have been shown to be effective, particularly for data with adequate temporal resolution. Here, despite the significant progress made over the last decade, there is still great need and potential for future work, including development of analytical techniques, reference materials and inter–laboratory comparisons, further exploration of N 2 O formation and destruction mechanisms, more observations across scales, and design and validation of interpretation and modelling approaches. Synthesizing all these efforts, we are confident that the N 2 O isotope community will continue to advance our understanding of N 2 O transformation processes in all spheres of the Earth, and in turn to gain improved constraints on regional and global budgets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) Version 4.0: User Manual

The IHEAT v4.0 software is a data reduction code for global thermography data acquired in the NASA Langley Aerothermodynamics Laboratory (LAL) hypersonic wind tunnels. IHEAT uses red and green color-intensity data from two-dimensional images of wind tunnel models to compute temperatures and heat-transfer rates using a semi-infinite, one-dimensional heat transfer approximation at each image pixel. Multiple automated tools in IHEAT v4.0 decrease the time required to reduce the data from a phosphor thermography wind tunnel run. Data at one or all of the image pixel locations can be exported to computer files for further analysis. The prior version of IHEAT, v3.2, was written in PV-WAVE® (now owned by Rogue Wave® Software) in 1994 and was limited in functionality to fit within the memory constraints of the available computers at the time. IHEAT v4.0 is written in MATLAB® by MathWorks® and contains several new features that leverage the increase in available memory of the current computers. A Piecewise tool permits the user to extract data along a segmented line cut that can follow interesting features in the image better than the single, straight line cuts that were possible with the legacy Length and Profile tools. The new Load Run and Batch tools facilitate batch processing by loading in all of the input files and images for a run at the same time. Load Run permits the user to process the available run images manually, while Batch automatically saves heat transfer data from all of the images based on the analysis previously performed on a single frame. IHEAT v4.0 also can automatically calculate the temporal collapse of reference line cuts from the time history heating data for a run to indicate the appropriate frame to reduce for each run. The IHEAT v4.0 source code was compiled into a standalone executable file that can be accessed remotely from several computers with different operating systems, simultaneously. The software is run through the MATLAB® Compiler Runtime engine, and therefore, IHEAT does not require a software license to run. Any software commands executed in the IHEAT v4.0 code will not affect other similar applications running on the same machine. Similarly, changes to the parent software do not affect a compiled code. These features of IHEAT v4.0 are improvements over the legacy v3.2 code, which required regular maintenance to avoid losing functionality as the PVWAVE ® programming language was upgraded.

Mason, Michelle L.↗

Cross-Linker Selection Controls Glass Transition Elevation or Reduction in Dynamic Covalently Bonded Polymer Networks

Introducing cross-links is a powerful approach to improve polymeric material performance relevant to controlling viscoelasticity, thermal and creep resistance, degradability, and efficient membrane separations. The chemically specific glass transition temperature T g is of fundamental importance in determining the time scales of key dynamical processes and physical state of the material in such applications. Here, we study experimentally how the introduction of relatively large cross-linking molecules in slowly exchanging dynamic bond-forming polymers (vitrimers) impacts vitrification for diverse polymer chemistries and a wide range of cross-link fractions. We find T g can increase, decrease, or even remain essentially unchanged, in qualitative contrast to the generic elevation of T g in traditional permanent polymer networks. We formulate an effective terpolymer network model to understand this rich behavior, which emerges as a consequence of a competition between pure cross-linking and generalized plasticization effects. The latter is associated with the tunable cross-linker size and intrinsic dynamic mobility that can offset slowing down due to traditional permanent cross-linking constraints. Here, a new strategy for functional polymer network design is suggested based on adjusting the relative importance of the two competing physical effects, which potentially can significantly enhance energy savings in applications while retaining other intrinsic properties germane to advanced materials performance.

Copolymers↗

Scaling Effects of Cr(VI) Reduction Kinetics. The Role of Geochemical Heterogeneity

The natural subsurface is highly heterogeneous with minerals distributed in different spatial patterns. Fundamental understanding of how mineral spatial distribution patterns regulate sorption process is important for predicting the transport and fate of chemicals. Existing studies about the sorption was carried out in well-mixed batch reactors or uniformly packed columns, with few data available on the effects of spatial heterogeneities. As a result, there is a lack of data and understanding on how spatial heterogeneities control sorption processes. In this project, we aim to understand and develop modeling capabilities to predict the sorption of Cr(VI), an omnipresent contaminant in natural systems due to its natural occurrence and industrial utilization. We systematically examine the role of spatial patterns of illite, a common clay, in determining the extent of transport limitation and scaling effects associated with Cr(VI) sorption capacity and kinetics using column experiments and reactive transport modeling. Our results showed that the sorbed mass and rates can differ by an order of magnitude due to of the illite spatial heterogeneities and transport limitation. With constraints from data, we also developed the capabilities of modeling Cr(VI) in heterogeneous media. The developed model is then utilized to understand the general principles that govern the relationship between sorption and connectivity, a key measure of the spatial pattern characteristics. This correlation can be used to estimate Cr(VI) sorption characteristics in heterogeneous porous media. Insights gained here bridge gaps between laboratory and field application in hydrogeology and geochemical field, and advance predictive understanding of reactive transport processes in the natural heterogeneous subsurface. We believe that these findings will be of interest to a large number of environmental geochemists and engineers, hydrogeologists, and those interested in contaminant fate and transport, water quality and water composition, and natural attenuation processes in natural systems.

58 GEOSCIENCES↗

Semiautomated head-and-neck IMRT planning using dose warping and scaling to robustly adapt plans in a knowledge database containing potentially suboptimal plans

Purpose: Prior work by the authors and other groups has studied the creation of automated intensity modulated radiotherapy (IMRT) plans of equivalent quality to those in a patient database of manually created clinical plans; those database plans provided guidance on the achievable sparing to organs-at-risk (OARs). However, in certain sites, such as head-and-neck, the clinical plans may not be sufficiently optimized because of anatomical complexity and clinical time constraints. This could lead to automated plans that suboptimally exploit OAR sparing. This work investigates a novel dose warping and scaling scheme that attempts to reduce effects of suboptimal sparing in clinical database plans, thus improving the quality of semiautomated head-and-neck cancer (HNC) plans. Methods: Knowledge-based radiotherapy (KBRT) plans for each of ten “query” patients were semiautomatically generated by identifying the most similar “match” patient in a database of 103 clinical manually created patient plans. The match patient’s plans were adapted to the query case by: (1) deforming the match beam fluences to suit the query target volume and (2) warping the match primary/boost dose distribution to suit the query geometry and using the warped distribution to generate query primary/boost optimization dose-volume constraints. Item (2) included a distance scaling factor to improve query OAR dose sparing with respect to the possibly suboptimal clinical match plan. To further compensate for a component plan of the match case (primary/boost) not optimally sparing OARs, the query dose volume constraints were reduced using a dose scaling factor to be the minimum from either (a) the warped component plan (primary or boost) dose distribution or (b) the warped total plan dose distribution (primary + boost) scaled in proportion to the ratio of component prescription dose to total prescription dose. The dose-volume constraints were used to plan the query case with no human intervention to adjust constraints during plan optimization. Results: KBRT and original clinical plans were dosimetrically equivalent for parotid glands (mean/median doses), spinal cord, and brainstem (maximum doses). KBRT plans significantly reduced larynx median doses (21.5 ± 6.6 Gy to 17.9 ± 3.9 Gy), and oral cavity mean (32.3 ± 6.2 Gy to 28.9 ± 5.4 Gy) and median (28.7 ± 5.7 Gy to 23.2 ± 5.3 Gy) doses. Doses to ipsilateral parotid gland, larynx, oral cavity, and brainstem were lower or equivalent in the KBRT plans for the majority of cases. By contrast, KBRT plans generated without the dose warping and dose scaling steps were not significantly different from the clinical plans. Conclusions: Fast, semiautomatically generated HNC IMRT plans adapted from existing plans in a clinical database can be of equivalent or better quality than manually created plans. The reductions in OAR doses in the semiautomated plans, compared to the clinical plans, indicate that the proposed dose warping and scaling method shows promise in mitigating the impact of suboptimal clinical plans.

60 APPLIED LIFE SCIENCES↗

SAM Code Enhancements for Fission Product Tracking of Noble Gases and Metals in MSRs

This report documents fiscal year 2026 enhancements to the System Analysis Module (SAM) for modeling fission product transport in liquid-fueled molten salt reactors (MSRs). The work advances three principal areas: noble gas transport, noble metal deposition, and user interface improvements. The noble gas transport capability integrates drift-flux gas transport, Henry’s law two-film interphase mass transfer with pressure-based nucleation suppression, Knudsen-regime pore diffusion into porous graphite with a conjugate salt-graphite interface constraint, built-in material properties, five Sherwood-number mass transfer correlations including three derived from high-fidelity NekRS simulations, and xenon-135 reactivity feedback through SAM’s point-kinetics model. This work also presents a comprehensive verification test suite, including new analytically verified cases for pressure-dependent onset of interphase gas transfer in a stagnant vertical pipe, a postulated FLiBe-graphite Xe extraction permeator, a gravity riser with a fission-product source, and a descending pipe with gas redissolution driven by hydrostatic pressure. A machine learning framework for bubble rise velocity prediction in molten salt systems is developed and benchmarked on molten-salt and diverse aqueous bubble datasets. The best-performing fine-tuned transfer-learning networks achieve an 82% reduction in RMSE relative to the Clift correlation, and is implemented directly in SAM. The noble metal transport capability is developed, including a liquid-wall deposition model and a gas-surface flotation mechanism that transfers insoluble particles entrained by sparging gas to wetted structures. Verification tests and demonstration cases cover the surface deposition, flotation efflux, and flotation shedding. Finally, a new [SpeciesTransport] input structure replaces positional global vectors with selfcontained, order-independent, named species blocks, simplifies the specification of multiphase species and decay chains, and remains fully compatible with existing SAM input files. Together, these developments improve the physical fidelity, verification basis, and usability of SAM for system-level analyses of fissionproduct behavior in MSRs.

Mui, Travis (ORCID:0000000303736470)↗

The impact of the LHC Z-boson transverse momentum data on PDF determinations

The LHC has recently released precise measurements of the transverse momentum distribution of the Z-boson that provide a unique constraint on the structure of the proton. Theoretical developments now allow the prediction of these observables through next-to-next-to-leading order (NNLO) in perturbative QCD. In this work we study the impact of incorporating these latest advances into a determination of parton distribution functions (PDFs) through NNLO including the recent ATLAS and CMS 7 TeV and 8 TeV p T Z data. We investigate the consistency of these measurements in a global fit to the available data and quantify the impact of including the p T Z distributions on the PDFs. Finally, the inclusion of these new data sets significantly reduces the uncertainties on select parton distributions and the corresponding parton-parton luminosities. In particular, we find that the p T Z data ultimately leads to a reduction of the PDF uncertainty on the gluon-fusion and vector-boson fusion Higgs production cross sections by about 30%, while keeping the central values nearly unchanged.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

In Situ Visualization and Production of Extract Databases

Simulations running at high concurrency on HPC systems generate large volumes of data that are impractical to write to disk due to time and storage constraints. Applications often adapt by saving data infrequently, resulting in datasets with poor temporal resolution. This can make datasets difficult to interpret during post hoc visualization and analysis, or worse, it can lead to lost science. In Situ visualization and analysis can enable efficient production of small data products such as rendered images or surface extracts that consist of polygonal geometry plus fields. These data products are far smaller than their source data and can be processed much more economically in a traditional post hoc workflow using far fewer computational resources. We used the SENSEI and Libsim in situ infrastructures to implement rendering workflow and surface data extraction workflows in the AVF-LESLIE combustion code. Finally, these workflows were then demonstrated at high levels of concurrency and showed significant data reductions and limited impact on the simulation runtime.

97 MATHEMATICS AND COMPUTING↗

Enhancement of the inherent self-protection of the fast sodium reactor cores with oxide fuel

With the development and research into the generation IV fast sodium reactors, great attention is paid to the enhancement of the core inherent self-protection characteristics. One of the problems dealt here is connected with the reduction of the reactivity margin so that the control rods running should not result in the core overheating and melting. In this paper we consider the possibilities of improving the core of BN-1200 with oxide fuel by a known method of introducing an axial fertile layer into the core. But unlike earlier studies this paper looks at the possibility of using such a layer not only for improving breeding, but also for reducing sodium void reactivity effect (SVRE). This proposed improvement of the BN-1200 core does not solve the problem of strong interference in control and protection system (CPS) rods of BN-1200, but they reduce significantly the reactivity margin for burn-up compensation. This helps compensate all the reactivity balances in the improved core configurations without violating constraints on SVRE value.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Structural Design Exploration of an Electric Powered Multi-Propulsor Wing Configuration

Advancements in aircraft electric propulsion may enable an expanded operational envelope for electrically powered vehicles compared to their internal combustion engine counterparts. High aspect ratio wings provide additional lift and drag reduction for a proposed multi-propulsor design, however, the challenge is to reduce the weight of wing structures while maintaining adequate structural and aeroelastic margins. Design exploration using a conventional design-and-build philosophy coupled with a finite element method (FEM)-based design of experiments (DOE) strategy are presented to examine high aspect ratio wing structures that have spanwise distributed electric motors. Multiple leading-edge-mounted engine masses presented a challenge to design a wing within acceptable limits for dynamic and aeroelastic stability. Because the first four primary bending eigenmodes of the proposed wing structure are very sensitive to outboard motor placement, safety-of-flight requirements drove the need for multiple spars, rib attachments, and outboard structural reinforcements in the design. Global aeroelasticity became an increasingly important design constraint during the on-going design process, with outboard motor pod flutter ultimately becoming a primary design constraint. Designers successively generated models to examine stress, dynamics, and aeroelasticity concurrently. This research specifically addressed satisfying multi-disciplinary design criteria to generate fluid-structure interaction solution sets, and produced high aspect ratio primary structure designs for the NASA Scalable Convergent Electric Propulsion Technology and Operations Research (SCEPTOR) project in the Aeronautic Research Mission Directorate at NASA. In this paper, a dynamics-driven, quasi-inverse design methodology is presented to address aerodynamic performance goals and structural challenges encountered for the SCEPTOR demonstrator vehicle. These results are compared with a traditional computer aided design based approach.

Moore, James B.↗

CMIP6 Historical Simulations (1850‐2014) with GISS‐E2.1

Simulations of the CMIP6 historical period 1850‐‐2014, characterized by the emergence of anthropogenic climate drivers like greenhouse gases, are presented for different configurations of the NASA Goddard Institute for Space Studies (GISS) Earth System ModelE2.1. The GISS‐E2.1 ensembles are more sensitive to forcing than their CMIP5 predecessors (GISS‐E2), but warm less during recent decades due to reduced total forcing. This forcing reduction is attributed to an increase in longwave opacity in pre‐industrial simulations, resulting in an atmosphere less sensitive to further increases in opacity that result from rising greenhouse gas concentrations. This demonstrates the importance of the base climatology to forcing and forced climate trends. Most model versions match observed temperature trends since 1979 from the ocean to the stratosphere. The choice of ocean model is important to the transient climate response, as found in CMIP5 GISS‐E2: the model that more efficiently exports heat to the deep ocean shows a smaller rise in tropospheric temperature. Model sea level rise over the historical period is traced to excessive drawdown of aquifers to meet irrigation demand with a smaller contribution from thermal expansion. This shows how fully coupled models can provide indirect observational constraints upon forcing, in this case, constraining irrigation rates with observed sea level changes. The overall agreement of GISS‐E2.1 with observed trends is familiar from evaluation of its predecessors, as is the conclusion that these trends are almost entirely anthropogenic in origin.

NASA Goddard Institute for Space Studies (GISS) Ea↗

Gate control of electron correlations towards Mott field effect transistors (MottFET)

The modulation of channel conductance in field-effect transistors (FETs) via metal-insulator-semiconductor structures has revolutionized information processing and storage. However, the limitations of silicon-based FETs in electrical switching have driven the search for new materials capable of overcoming these constraints. Electrostatic gating of competing electronic phases in a Mott material near its metal-to-insulator transition (MIT) offers the prospects of substantial modulation of the conducting electrons and electrical resistivity through small changes in band filling. While electrostatic control of the MIT has been previously reported, the advancement of Mott materials toward novel Mott-based transistors, MottFETs requires the realization of their unique physical properties in a solid-state device. In this study, we present gate control of electron correlation using a solid-state device utilizing the oxide Mott system La 1-x Sr x VO 3 as a correlated FET channel. We report on a gate resistance response that cannot be explained in a purely electrostatic framework. This behavior suggests an enhancement in effective mass and a reduction in effective carrier density as the system approaches its insulating state, consistent with theoretical predictions for Mott systems, suggesting at least 100× charge gain originating from the correlated behavior. These preliminary results pave the way toward the development of highly efficient, low-power electronic devices that could surpass the performance bottlenecks of conventional FETs by leveraging the electronic phase transitions of correlated electron systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Rolling Horizon with K-Position Search Method for Strategic Deconfliction of Package Delivery UAS

This research focuses on the strategic deconfliction of unmanned aircraft systems (UAS) in an urban package delivery environment with two depots and multiple drop-off locations. Since the formulated mixed-integer nonlinear programming (MINLP) problem is non-deterministic polynomial-time (NP) hard, a heuristic algorithm called "rolling horizon with k-position search (KPS)" is used to compute the departure sequence and scheduled time of departure (STD) of each UAS at a depot, considering temporal constraints at en-route crossing waypoints and depots for strategic deconfliction. The simulation studies show that an increase in the value of k (local neighborhood search) in the KPS reduces the average ground delay at the cost of an increase in the computation time for a given number of UAS, size of the rolling horizon window, and number of depots involved in the local neighborhood search. The studies also show that for a given rolling horizon window, the computation time increases exponentially with an increase in the total number of UAS flights when serial processing the local neighborhood search of KPS (with k > 1) and drops by an order of magnitude upon performing the local neighborhood search of KPS using parallel processing instead of serial processing. The computation time drops with the reduction in air traffic complexity of a scenario for a given number of flights, k (local neighborhood search), and rolling horizon window.

UTM↗

150 Shades of Green: Using the Full Spectrum of Remote Sensing Reflectance to Elucidate Color Shifts in the Ocean

This article proposes a simple and intuitive classification system by which to define full spectral remote sensing reflectance (Rrs(λ)) data with a quantitative output that enables a more manageable handling of spectral information for aquatic science applications. The weighted harmonic mean of the Rrs(λ) wavelengths outputs an Apparent Visible Wavelength (in units of nanometers), representing a one-dimensional geophysical metric of color that is inherently correlated to spectral shape. This dimensionality reduction of spectral information combined with the output along a continuum of wavelength values offers a robust and user-friendly means to describe and analyze spectral Rrs(λ) in terms of spatial and temporal trends and variability. The uncertainty in the algorithm's estimation of spectral shape is demonstrated on a global scale, in addition to the utility of the algorithm to discern spectral-spatial-temporal trends in the ocean, on a per-pixel basis for the entire 22 year continuous ocean color (SeaWiFS and MODIS-Aqua) time-series. This technique can be applied to datasets of varying multi- and hyper-spectral resolutions, providing continuity between heritage and future satellite sensors, and further enabling an effective means of elucidating similarities or differences in complex spectral signatures within the constraints of two dimensions. This straightforward means of conceptualizing multi-dimensional variability can help maximize the potential of the spectral information embedded in remote sensing data.

ocean color↗

Data-driven simultaneous process optimization and adsorbent selection for vacuum pressure swing adsorption

Technologies for post-combustion carbon capture are essential for the reduction of greenhouse gas emissions to the atmosphere. However, they are still associated with high costs and energy consumption. Intensified processes for carbon capture have the potential to overcome these challenges due to their higher efficiency, lower capital cost, and increased operational flexibility. Here, this work investigates simultaneous optimization of process conditions and adsorbent selection for a modular Vacuum Pressure-Swing Adsorption system designed for CO 2 capture. Both surrogate-based Nonlinear Programming and Mixed-Integer Nonlinear Programming approaches are applied and compared in terms of computational efficiency and solution accuracy. Moreover, process performance results are examined by applying several data analytics techniques to gain insights into the material-process correlations. Data-driven classifiers and neural networks can accurately predict whether a material is likely to satisfy purity, recovery, and energy constraints when operated at optimal process conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗