Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data shift”

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 685 records · Page 38

Aragonite saturation horizon variability along North Pacific seamounts and implications for deep-sea coral reefs

The 2014 discovery of living deep-sea coral reefs along the Northwest Hawaiian Islands (NWHI) and lower Emperor Seamount Chain (ESC), despite the North Pacific’s shallow aragonite saturation horizon (ASH) and high CaCO3 dissolution rates, underscores the need to understand the local seawater chemistry that allows these reefs to persist. We investigated seawater carbonate chemistry using discrete samples along the NWHI and ESC from two cruises ~1 year apart (08/26/21 – 09/26/21, 09/09/22 – 10/24/22). Across the two cruises, ASH depth difference ranged from 15 to 77 m. Since the Pacific ASH shoals by 1–2 m yr?¹, this long-term trend cannot explain the magnitude of ASH change observed between cruises. Temperature-salinity plots similarly indicate no major shifts in intermediate water masses that could account for these changes. Instead, ASH depth variability was primarily governed by localized biogeochemical processes, namely changes in intermediate water respiration and CaCO3 dissolution. Indicators for dissolution (TA*) and respiration (AOU) suggest changes in ASH depth were driven by changes in dissolution at the northern- and southern-most sites, whereas respiration exerted stronger control at central sites. Combining 2021 and 2022 data with data from 2014 – 2019 (excluding 2018) revealed high interannual ASH variability, by as much as >200 m at one site. Deep-sea coral reefs across the NWHI and ESC currently reside close to the ASH depth and likely experience seasonal and interannual shifts between under- and supersaturation. As ocean acidification progresses however, persistent exposure to undersaturated seawater could further threaten these critical deep-sea ecosystems.

coral reefs↗

Density Dependence in Three Snake River Sockeye Salmon Nursery Lakes in Central Idaho

Abstract Snake River Sockeye Salmon Oncorhynchus nerka, listed as an endangered species in 1991, currently inhabit three nursery lakes (Redfish, Pettit, and Alturas lakes) in the Sawtooth Valley, Idaho. Conspecific kokanee (lacustrine Sockeye Salmon) are also present in the lakes. Snake River Sockeye Salmon recovery efforts, initially focused on genetic conservation, are now attempting to rebuild naturally spawning populations using hatchery supplementation. However, in Sockeye Salmon nursery lakes, density dependence is frequently observed when elevated O. nerka abundance leads to declines in zooplankton biomass, body size, and shifts in community composition. In turn, these changes lead to reductions in juvenile O. nerka growth rates, survival, and adult returns. We examined a long-term data set of O. nerka population metrics and associated zooplankton community metrics. We found evidence of density dependence within and among nursery lakes. We detected differences in zooplankton biomass, lengths of preferred zooplankton prey (Daphnia spp. and cyclopoid copepods), parr growth rates, and age-1 smolt size among the three lakes. We found negative relationships between O. nerka density and zooplankton biomass and size. We identified positive relationships between zooplankton biomass and two response variables: smolt size at migration and growth rates of hatchery parr. The relationships were generally similar among lakes. Variable outcomes were a result of differences in O. nerka density (or zooplankton biomass), controlled primarily by the relative proportion of spawning and rearing habitat in each lake. Understanding unique lake habitats, ecological interactions, and the role of density dependence is germane to management of Snake River Sockeye Salmon populations.

Griswold, Robert G.↗

Vulnerability and resilience of urban energy ecosystems to extreme climate events: A systematic review and perspectives

We reviewed the present studies on the vulnerability and resilience of the energy ecosystem (most parts of the energy ecosystem), considering extreme climate events. This study revealed that the increased interactions formed during the transformation of the energy landscape into an ecosystem could notably increase the vulnerability of the energy infrastructure. Such complex ecosystem cannot be assessed using the present state of the art models used by the energy system modelers. Therefore, this study introduces a novel analogy known as the COVID analogy to understand the propagation of disruption within and beyond the energy ecosystem and organized the present state of the art based on the COVID analogy. The analogy helps to categorize the vulnerability of the energy infrastructure into three stages. The study revealed that although there are many publications covering the vulnerability and resilience of the energy infrastructure, considering extreme climate events, the majority are focused on the direct impact of extreme climate on the energy ecosystem. In addition, most of the studies do not consider the impact of future climate variations during this assessment. The propagation of disruptions was assessed mainly for wildfires and hurricanes. Further, there is a clear research gap in considering vulnerability assessment for interconnected energy infrastructure. Here, the transformation of energy systems into a complex ecosystem notably increases the complexity, making it difficult to assess vulnerability and resilience. A shift from a centralized to decentralized modeling architecture could be beneficial when considering the complexities brought by that transformation. Hybrid models consisting of both physical and data-driven machine learning techniques could also be beneficial in this context.

54 ENVIRONMENTAL SCIENCES↗

Venturing into Unexplored Phase Space: Synthesis, Structure, and Properties of MgCo 3 B 2 Featuring a Rumpled Kagomé Network

MgCo 3 B 2 , a novel ternary boride in a previously unexplored phase space, was synthesized using the hydride route. In situ powder X-ray diffraction and DFT calculations aided in the discovery of this compound, whose structure was then determined by single-crystal X-ray diffraction. Like the closely related CeCo 3 B 2 , MgCo 3 B 2 crystallizes in centrosymmetric space group P6/mmm (a = 4.883(2) Å, c = 2.926(2) Å at 210 K, Z = 1). Unlike CeCo 3 B 2 , however, it adopts a disordered structure that features a rumpled Kagomé network of Co atoms, and Mg atoms fill the channels of a Co–B framework. Although the structural disorder leads to motifs that are similar to those observed in MgNi 3 B 2 and other related ternary borides, no evidence of an ordered superstructure was found by single-crystal X-ray diffraction or high-resolution powder X-ray diffraction. In the case of CeCo 3 B 2 , boron atoms occupy the center of regular Co 6 trigonal prisms; in MgCo 3 B 2 , boron atoms are shifted from the center of the prism to form B–B dimers with roughly the same length as those found in MgNi 3 B 2 . Magnetic susceptibility data exhibit an unusual temperature dependence that cannot be convincingly modeled by the modified Curie–Weiss equation, consistent with DFT calculations predicting a nonmagnetic ground state. Intrinsic susceptibility at 300 K is 1.42 × 10 –3 emu/mol Oe, which is comparable to that of paramagnetic YCo 3 B 2 and CeCo 3 B 2 with a similar structure and composition. Here, this study showcases the efficacy of combining several methodologies to discover new solids in unexplored phase spaces. This approach includes in situ PXRD data to monitor reactions of precursors upon heating, a diffusion-enhanced synthesis method, and DFT assessment of compound stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Heavy Versus Light Lanthanide Selectivity for Graphene Oxide Films is Concentration Dependent

Rare earths are important materials in various technologies such as catalysis and optoelectronics. Graphene oxide (GO) is a promising material for separation applications, including the isolation of lanthanides from complex mixtures. Previous works using fatty acid monolayers have demonstrated preferential heavy versus light lanthanide adsorption, which has been attributed to differences in lanthanide ion size. In this work, we used interfacial X-ray fluorescence measurements to reveal that GO thin films at the air/water interface have no lanthanide selectivity for dilute subphases. However, at high subphase concentrations, ~8 times more Lu is adsorbed than La. By comparing the GO results with an ideal monolayer with a carboxylic acid headgroup, arachidic acid (AA), we demonstrate that the number of Lu ions adsorbed to GO is significantly higher than the number expected to compensate for the surface charge. Vibrational sum frequency generation (SFG) spectroscopy results on both GO thin films and AA monolayers reveal a red-shifted SFG signal in the OH region, which we attribute to partial dehydration of the adsorbed ions and carboxylic acid headgroups. Liquid surface X-ray reflectivity data show that the GO thin film structure does not significantly change between the very dilute and concentrated subphases. We speculate that the functional groups of both GO and AA facilitate cation dehydration, which is essential for ion adsorption. Heavy lanthanide Lu has stronger ion–ion correlations that can overcome the electrostatic repulsion between cations at higher concentrations compared to light lanthanide La, meaning GO and AA can exhibit apparent overcharge with Lu. Lastly, the layered structure of the GO films and reactive chemical nature of GO itself can accommodate ion adsorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Uncovering the phonon spectra and lattice dynamics of plastically deformable InSe van der Waals crystals

Stacking two-dimensional (2D) van der Waals (vdW) materials in a layered bulk structure provides an appealing platform for the emergence of exotic physical properties. As a vdW crystal with exceptional plasticity, InSe offers the opportunity to explore various effects arising from the coupling of its peculiar mechanical behaviors and other physical properties. Here, we employ neutron scattering techniques to investigate the correlations of plastic interlayer slip, lattice anharmonicity, and thermal transport in InSe crystals. Not only are the interlayer slip direction and magnitude well captured by shifts in the Bragg reflections, but we also observe a deviation from the expected Debye behaviour in the heat capacity and lattice thermal conductivity. Combining the experimental data with first-principles calculations, we tentatively attribute the observed evidence of strong phonon-phonon interactions to a combination of a large acoustic-optical frequency resonance and a nesting effect. These findings correlate the macroscopic plastic slip and the microscopic lattice dynamics, providing insights into the mechano-thermo coupling and modulation in 2D vdW materials.

36 MATERIALS SCIENCE↗

From primordial clocks to circadian oscillators

Circadian rhythms play an essential part in many biological processes, and only three prokaryotic proteins are required to constitute a true post-translational circadian oscillator1. The evolutionary history of the three Kai proteins indicates that KaiC is the oldest member and a central component of the clock. Subsequent additions of KaiB and KaiA regulate the phosphorylation state of KaiC for time synchronization. The canonical KaiABC system in cyanobacteria is well understood but little is known about more ancient systems that only possess KaiBC. However, there are reports that they might exhibit a basic, hourglass-like timekeeping mechanism. Here we investigate the primordial circadian clock in Rhodobacter sphaeroides , which contains only KaiBC, to elucidate its inner workings despite missing KaiA. Using a combination of X-ray crystallography and cryogenic electron microscopy, we find a new dodecameric fold for KaiC, in which two hexamers are held together by a coiled-coil bundle of 12 helices. This interaction is formed by the carboxy-terminal extension of KaiC and serves as an ancient regulatory moiety that is later superseded by KaiA. A coiled-coil register shift between daytime and night-time conformations is connected to phosphorylation sites through a long-range allosteric network that spans over 140 Å. Our kinetic data identify the difference in the ATP-to-ADP ratio between day and night as the environmental cue that drives the clock. They also unravel mechanistic details that shed light on the evolution of self-sustained oscillators.

59 BASIC BIOLOGICAL SCIENCES↗

Time-dependent experimental identification of inter-ELM microtearing modes in the tokamak edge on DIII-D

In a series of discharges on the DIII-D tokamak, fast vertical plasma jogs are used to induce current perturbations in the steep gradient region of the H-mode edge. These current perturbations directly influence the edge q profile, decoupling the resonant location and instability drive of pedestal-localized microtearing modes (MTMs.) By exploiting this effect, we develop and apply a new experimental technique to track the dynamical frequency evolution of MTMs in the pedestal region, providing a compelling validation of the MTM model. The frequency of potential MTMs is calculated as the Doppler-shifted electron diamagnetic frequency at rational q=m/n surfaces, showing remarkable agreement with chirped frequency behavior of n=3, 4 and 5 modes detected with fast magnetics. Data is collected throughout multiple ELM cycles in order to build robust statistics describing the time-dependent frequency evolution of MTMs, which can be explained by examining the recovery of pedestal gradients after an ELM event. MTMs have a dominant transport contribution in the electron thermal channel, so the presented results indicate that reduced models of pedestal transport must be electromagnetic in nature and constructed with accurate calculations of MTM stability; inclusion of this physics is essential for accurate predictions of the electron temperature pedestal profile. Supporting measurements of mode saturation, propagation direction and transport fingerprints are made to support the dynamic frequency determination, unambiguously and experimentally identifying MTMs in the pedestal region of DIII-D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Solvent organization in the ultrahigh-resolution crystal structure of crambin at room temperature

Ultrahigh-resolution structures provide unprecedented details about protein dynamics, hydrogen bonding and solvent networks. The reported 0.70 Å, room-temperature crystal structure of crambin is the highest-resolution ambient-temperature structure of a protein achieved to date. Sufficient data were collected to enable unrestrained refinement of the protein and associated solvent networks using SHELXL . Dynamic solvent networks resulting from alternative side-chain conformations and shifts in water positions are revealed, demonstrating that polypeptide flexibility and formation of clathrate-type structures at hydrophobic surfaces are the key features endowing crambin crystals with extraordinary diffraction power.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Direct Numerical Simulation of Transitional and Turbulent Flows Over Multi-Scale Surface Roughness—Part II: The Effect of Roughness on the Performance of a High-Pressure Turbine Blade

Abstract Turbine blades generally present surface roughness introduced in the manufacturing process or caused by in-service degradation, which can have a significant impact on aero-thermal performance. A better understanding of the fundamental physical mechanisms arising from the interaction between the roughness and the turbine flow at engine-relevant conditions can provide insights for the design of blades with improved efficiency and longer operational life. To this end, a high-fidelity numerical framework combining a well-validated solver for direct numerical simulation and a second-order accurate immersed boundary method is employed to predict roughness-induced aero-thermal effects on an LS89 high-pressure turbine (HPT) blade at engine-relevant conditions. Different amplitudes and distributions of surface roughness are investigated and a reference smooth-blade simulation under the same flow conditions is conducted for comparison. Roughness of increasing amplitude progressively shifts the blade suction side boundary layer transition upstream, producing larger values of the turbulent kinetic energy and higher total wake losses. The on-surface data-capturing capabilities of the numerical framework provide direct measurements of the heat flux and the skin friction coefficient, hence offering quantitative information between the surface topology and engineering-relevant performance parameters. This work may provide a benchmark for future numerical studies of turbomachinery flows with roughness.

Engineering↗

29Si solid state NMR and Ti K-edge XAFS pre-edge spectroscopy reveal complex behavior of Ti in silicate melts

Abstract An understanding of the mechanisms of Ti is incorporation into silicate glasses and melts is critical for the field of petrology. Trace-element thermobarometry, high-field-strength element partitioning, and the physical properties of magmas are all be influenced by Ti incorporation into glasses and changes therein in response to changes in composition and temperature. In this study, we combine 29 Si solid state NMR and Ti K -edge XAFS spectroscopy to investigate how Ti is incorporated into quenched Na-silicate glasses, and the influence of Ti on the structure of silicate species in these glasses. 29 Si NMR shows that in both Ti-bearing Na 2 O•4SiO 2 (NS4) and Na 2 O•8SiO 2 (NS8) glasses, increasing the amount of Ti in the melt results in a shift of Si Q 4 peak in the 29 Si NMR spectra reflecting Ti nearest neighbors for Si in Q 4 speciation. The Ti XAFS results from NS8 glass indicate that Ti is primarily incorporated in [5]-fold coordination. At higher Ti content, there is a shift of the XAFS pre-edge feature suggesting mixing of [4]-fold Ti into the spectra. Combined, the 29 Si NMR and XAFS pre-edge data are consistent with Ti incorporation as isolated [5] Ti atoms and the formation of [5] Ti clusters at relatively low Ti concentrations, with no evidence for Ti–Na interactions as suggested by previous studies. As the Ti content increases, the Ti atoms begin to occupy 4-fold coordinated sites interacting primarily with Si in Q 4 speciation (no significant Na– [4] Ti bonding). The internal consistency of these two techniques provides a uniquely complete snapshot of the complexity of Ti incorporation in silicate melts and underlies the importance of understanding Ti incorporation mechanisms in natural magmatic systems.

Ackerson, Michael R.↗

A chemical kinetics theory for interpreting the non-monotonic temperature dependence of enzymatic reactions

Abstract. One notable observation of enzymatic chemical reactions is that, for a given abundance of enzymes and substrates, temperature increases cause reaction rates to first increase consistent with the Arrhenius relationship, then plateau, and finally fall off quickly to zero at high temperatures. While many mathematical functions have been used to describe this pattern, we here propose a chemical kinetics theory which successfully replicates this observation and provides insights into the processes responsible for these dynamics. The chemical kinetics theory combines the law of mass action, von Smoluchowski's diffusion-limited chemical reaction theory, and Eyring's transition state theory. This new theory reveals that the thermally reversible enzyme denaturation ensured by the ceaseless thermal motion of molecules and ions in an enzyme solution explains the plateau and subsequent decrease in chemical reaction rates with increasing temperature. The temperature-dependent affinity parameter (K) that relates enzymes and substrates through their binding also affects the shape of the emergent temperature response. We demonstrate that with an increase in substrate availability, K shifts the optimal temperature, where reaction rates plateau, towards higher values. Further, we show that the chemical kinetics theory accurately represents 12 sets of published enzyme assay data and includes the popular mechanistic model by Ratkowsky et al. (2005) as a special case. Given its good performance and solid theoretical underpinning, we believe this new theory will facilitate the construction of more mechanistic-based environmental biogeochemical models.

Tang, Jinyun↗

Generalizing synthetic data-trained acoustic predictive models to real-world measurements

Acoustic Resonance Spectroscopy (ARS) is highly sensitive to structural properties such as material, geometry, and environmental conditions; as a consequence, it can noninvasively measure internal properties that are unobservable by most other methods. Because of its sensing capabilities and low implementation cost and complexity, ARS has potential as a paradigm shift in noninvasive sensing, characterization, and monitoring applications. However, extracting specific properties from ARS measurements, comprising the vibration spectrum of a test object, is challenging due to the sensitivity of the spectra to other structural changes not being measured, e.g. manufacturing tolerances, component coupling, environmental variation, etc. Neural Networks are promising tools for identifying trends in ARS measurements, but their training typically requires large datasets, which are often impractical to obtain for real-world systems. Synthetic data can be simulated efficiently, but discrepancies between synthetic and real-world data frequently lead to poor generalization when testing on the real-world data. We propose a novel ARS model training framework that enables networks trained exclusively on synthetic ARS data to generalize effectively to real-world measurements. Our approach leverages the Correlation Alignment (CORAL) technique to enforce the extraction of features common to both synthetic and real-world domains. As a case study, we demonstrate noninvasive ARS-based pressure measurements in sealed systems. Finite element method (FEM) simulations were used to generate synthetic training data across diverse vessel configurations and pressure conditions, and model performance was then tested on real-world measurements. We demonstrate that robust machine learning models for ARS can be developed without large real-world datasets, significantly broadening the applicability of ARS for noninvasive sensing. Moreover, the approach is extensible to other sensing modalities where synthetic data are abundant but real-world data are limited.

36 MATERIALS SCIENCE↗

A Grassroots Network and Community Roadmap for Interconnected Autonomous Science Laboratories for Accelerated Discovery

Scientific discovery is being revolutionized by AI and autonomous systems, yet current autonomous laboratories remain isolated islands unable to collaborate across institutions. We present the Autonomous Interconnected Science Lab Ecosystem (AISLE), a grassroots network transforming fragmented capabilities into a unified system that shorten the path from ideation to innovation to impact and accelerates discovery from decades to months. AISLE addresses five critical dimensions: (1) cross-institutional equipment orchestration, (2) intelligent data management with FAIR compliance, (3) AI-agent driven orchestration grounded in scientific principles, (4) interoperable agent communication interfaces, and (5) AI/ML-integrated scientific education. By connecting autonomous agents across institutional boundaries, autonomous science can unlock research spaces inaccessible to traditional approaches while democratizing cutting-edge technologies. This paradigm shift toward collaborative autonomous science promises breakthroughs in sustainable energy, materials development, and public health.

Ferreira da Silva, Rafael [Oak Ridge National Labo↗

The persistence and conversion of coastal foredune and swale vegetation community distributions 63 years later

Vegetation shifts can directly alter habitat dynamics and indirectly impact habitat stability relative to disturbance response. Barrier island dune habitats exhibit spatiotemporally dynamic topography that is affected by vegetation. However, vegetation distribution data can be rare and vegetation persistence is largely unknown such that species turnover over in communities can occur unnoticed. This is true despite concerns and documented cases of woody encroachment related to climate change in these ecogeomorphic habitats where physical stability to resist storm erosion varies with vegetation distribution and density. In 1956 and 1957, the vegetation of Island Beach State Park, NJ, was mapped as a permanent record for subsequent ecological study. In June 2020, we remapped the vegetation of 5.4 of 17 km north to south, seaward of the thicket community boundary. We maintained the same classification system as the historic record, physically mapping vegetation patches via GPS. We quantified changes in thicket, heather, and grass community distribution between the two time periods. Habitat persistence and conversion varied in the 63 years. Heath communities saw 80%–97% habitat loss in conversion to woody thicket. Conversely, thicket community distribution drastically increased, replacing heath where it was previously prevalent. This represents the first known documented instances of woody encroachment for Morella pensylvanica. When they did not expand, thicket communities receded landward or underwent turnover to an invasive species. Woody species of interest for dune stabilization occupied areas of similar habitat characteristics. Dune vegetation distribution persistence from 1957 to 2020 was relatively consistent and stable with the exception of heath habitat conversion. Barrier island stability is directly related to vegetation stability such that understanding where community shifts might occur over time can aid in managing and modeling efforts surrounding these dynamic ecogeomorphic habitats.

54 ENVIRONMENTAL SCIENCES↗

Dynamic time-warping correction for shifts in ultrahigh resolving power ion mobility spectrometry and structures for lossless ion manipulations

Detection of arrival time shifts between ion mobility spectrometry (IMS) separations can limit achievable resolving power (Rp), particularly when multiple separations are summed or averaged, as commonly practiced. Such variations are more apparent in higher Rp measurements, and are particularly evident in long path length traveling wave structures for lossless ion manipulations (SLIM) IMS due to their typically much longer separation times. Here we explore the utility of a data processing approaches employing linear alignment (LA) and nonlinear dynamic time warping (DTW) of IMS separations to correct for variations between separations, such as due to pressure fluctuations. For multipass SLIM IMS separations, where narrow mobility range measurements have arrival times that can extend to several seconds, the LA approach effectively corrected for such variations, and significantly improvement Rp for summed separations. However, LA was much less effective for high Rp broad mobility range separations, such as obtained with multilevel SLIM IMS. Changes in IMS arrival times ions were observed to be correlated with small pressure changes, with approximately 0.6% relative arrival time shifts being common, sufficient to result in a loss of Rp for summed separations. Comparison of the approaches showed DTW alignment performed similarly to LA when used over a narrow mobility range, but was significantly better (providing narrower peaks and higher signal intensities) for wide mobility range data. We found the DTW approach increased Rp by as much as 115% for measurements in which 50 IMS separations over 2 seconds were summed, and leading to a large improvement in effective Rp. We conclude that DTW is superior to LA for ultrahigh resolution broad mobility range SLIM IMS separations, correcting for ion arrival time shifts regardless of the cause. Our tool is publicly available for use with universal ion mobility format (.UIMF) and text (.txt) files.

Data alignment, dynamic time warping, ion mobility↗

On phosphorus chemical shift anisotropy in metal (IV) phosphates and phosphonates: A 31 P NMR experimental study

The phosphorus chemical shift anisotropies, 31 PΔcs, and asymmetry parameters η were measured by the 31 P{ 1 H} NMR experiments in static and low-frequency spinning samples of the zirconium phosphates and phosphonates and also in the mixed Zr (IV)/Sn (IV) phosphate/phosphonate material. The data obtained have shown a 111 connectivity in the HPO 4 and PO 3 groups, which does not change at modification and intercalation of the materials. The 31 PΔcs values of the phosphonate groups (43–49 ppm) significantly surpass the values characterizing the HPO 4 groups (23–37 ppm). The 31 P Δcs values obtained for the metal (IV) phosphates were discussed in terms of P-O distances. Finally, the 31 P chemical shift anisotropy parameters can help at elucidation of local structures in phosphate and phosphonate materials.

1H MAS NMR↗

Mobility Data and Models Informing Smart Cities

This presentation explores the interactions of Emerging Technology, Changing Urban Environments, and Urban Travel Behavior on Mobility and Energy Impacts. Key findings include quantifying impacts of emerging mobility, access and infrastructure associated with new mobility choices and services in urban areas. The results demonstrate new data collection methods and capabilities to understand and identify key levers to improve energy productivity of future mobility systems and of quickly evolving MaaS and COVID-19 contexts to monitor rapidly shifting urban mobility patterns. Under development are mode choice models for new modes versus traditional modes. Initial estimates are developed on the potential of workforce mobility strategies in shaping future energy-efficient mobility system impacts. For mode replacement and workforce mobility, this presentation offers observability into the changes in number of transactions per mode, after ride-hailing/TNC/MaaS introduction and in origins of workforce to enable user need-driven reimagining of efficient mobility systems: Seattle (SEA-TAC) airport: for every 100 new TNC transactions for ground transportation, ~27% replaced transit, 35% replaced parking, 17% replaced car rentals, and 21% replaced taxis. Similarly, at Denver International (DEN), ride-hailing transactions replaced transit, parking, car rental and taxis at a rate of 34.7%, 39.0%, 16.6%, and 9.7%, respectively. A workforce mobility tool, analysis/visualization techniques, and capabilities to understand and identify key job commute needs, new choices in access to job opportunities, and affordability aspects as levers to improve energy productivity of future integrated urban mobility systems.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗