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This webinar describes linkages between NREL's dGen, SAM, and REopt tools that were developed as a part of the RiDER project, including specifying utility rates in the SAM GUI and using them in dGen adoption analysis, and using REopt to determine optimal system sizes for dGen agents.
The National Renewable Energy Laboratory (NREL) uses the Mobility Energy Productivity (MEP) as a metric and a lens to guide applied research into high performance public mobility. In the current initiative to abate global warming, the US needs not only zero-emission vehicles in the transit fleet (such as buses and shuttles) but also time- and cost-effective services to connect people with goods, services and employment toward a high-quality of life. Our current transportation system is overly dependent on personally-owned automobiles for high quality mobility, with public modes being less viable in many areas. Simply electrifying the drivetrains of existing public transit modes will fail to improve the quality of mobility for those that do not have access to private automobiles. The slow rebound by transit from the pandemic reveals the need to reinvent public transit service. Using the MEP lens, NREL researchers have tracked various novel developments in the public mobility space, with the confluence of shared, on-demand transit (ODT) services using light duty vehicles emerging as a key enabler of high-efficiency public mobility. Deployments such as those in Arlington, TX, Dallas, TX, Fort Erie, ON, and Innisfil, ON showcase the use of fleets of light-duty vehicles as the basis for community circulation and first/last mile to intra-regional transit. ODT services have demonstrated improvements in being more time efficient for riders, more energy efficient in operation (even before the introduction of fully electric vehicles), as well as being cost effective. It appears that aspects of the long-awaited promise of Personal Rapid Transit from the 1970s are beginning to be realized through ODT deployments, leveraging transportation network company (TNC) logistics, popularized by Uber and Lyft, but applied to public mobility. Currently, manually driven ODT operations are already cost competitive with traditional transit systems on a cost per ride basis, and full automation promises to reduce costs by 50% while providing additional safety and verified customer service. Connecting these ODT systems with efficient and effective intra-regional backbone transit service is the next step, with transit agencies like DART providing early results. This discussion will walk through the evidence for this postulated outcome and show results from a series of case-studies.
Dynamic ride-sharing (DRS) has been projected to be a key solution to lowering system-wide congestion. Despite recent developmental progress, demand studies for DRS suggest low levels of willingness for travelers to use such services. The disconnect between DRS system designs and user preferences limits the application impacts of DRS in the real world. Therefore, this paper aims to design a new DRS trip/vehicle assignment strategy by considering the user preferences of choices under different levels of service. In this study, an agent-based simulation approach is used to model a fleet of shared vehicles that allows DRS. An optimization model is developed to match riders to vehicles while accounting for traveler delay and delay acceptance. Travelers are also dynamically issued predictive discounts, catered to their expected willingness to pay, to incentivize them to accept longer trip delays. Results show that the proposed approach can improve system efficiency by increasing average vehicle occupancy by up to 1.0 persons/trip and DRS acceptance by up to 38.9% depending on fleet size. Additionally, congestion is eased through the decrease of empty vehicle miles traveled by up to 7.1%.
This dissertation explores factors influencing pooled rideshare (PR) adoption to provide actionable insights for transportation network companies (TNCs) and policymakers. PR allows travelers to share rides with unknown passengers, offering benefits such as cost reduction and congestion relief. However, adoption remains limited due to safety concerns, privacy issues, and trust in rideshare platforms. A national U.S. survey with 5,385 respondents examined transportation preferences and barriers to PR adoption. Exploratory and confirmatory factor analyses identified five key factors influencing PR consideration—safety, service experience, privacy, traffic/environment, and time/cost. Second factor analyses examined ways to optimize PR experiences, revealing four factors—comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety. Privacy concerns, for instance, using regression analysis, were found to reduce the likelihood of PR adoption by 77%, and convenience had the potential to increase it by 156%. The Pooled Rideshare Acceptance Model (PRAM), based on the Technology Acceptance Model, assessed the impact of these factors using the Structural Equation Model (SEM). Privacy, safety, trust, and convenience had a large effect (Cohen's f2 > 0.35) on PR acceptance, while multigroup analyses (PRAMMA) explored 16 demographic variables such as gender, generation, and income, emphasizing the need for tailored strategies. Based on all the statistical analysis and workshops using descriptive statistics, 95 actionable recommendations were made from the riders' perspective. Findings highlight the importance of customized services, user experience improvements, and policy interventions to enhance PR adoption. This dissertation provides a roadmap for future research and policy development, ensuring evidence-based, practical strategies to improve PR services in the U.S. and beyond.
This dissertation explores the study the integration of human factors modeling and rideshare fleet control algorithms. Pooled rideshare is a unique transportation mode offering that allows riders increased flexibility and accessibility over public transportation, and decreased cost relative to personal vehicles or traditional rideshare. Additionally, relative to personal vehicles, pooled rideshare offers reduced costs and options for those with difficulty obtaining transportation. Prior research in the space typically focused on modeling human behavior, or optimizing system performance, but a lack of integration of the concepts leads to unrealistic or underutilized outcomes. To tackle this problem, novel rideshare assignment, and repositioning strategies were designed and implemented in a simulation environment. Through a series of successive studies, improvements to current rideshare processes were identified, and beneficial outcomes for profitability, accessibility, and traffic were explored. Further, improved metrics to assess rideshare performance were designed and analyzed in the context of improved rideshare offerings. This research contributes to the field of transportation by tackling novel but pragmatic approaches to challenges facing the rideshare industry. Through the course of this dissertation, rideshares impacts on users, operators, and even regulators will be explored in detail. The justification behind the use of a simulation environment, a set of simulated regional models for testing, and the focus on realism and deployability is illustrated. The research identifies holes in potential markets for the use of both private, and public rideshare systems.
The U.S. Department of Energy's National Laboratory of the Rockies works in partnership with communities and transit agencies across North America to support and evaluate customized on-demand transit (ODT) systems. ODT, also known as on-demand mobility or microtransit, is a flexible form of public mobility. Unlike traditional fixed-route transit, ODT adjusts where and when service is provided rather than following predetermined schedules and routes. Having evolved from commercial ride-hailing business models, ODT leverages smartphone connectivity and real-time route optimization to provide highly responsive and dynamic service. ODT trips, which are usually shared, can function as a standalone service or as a first-/last-mile service connecting riders to other types of transit.
Shared Mobility Inc. (SMI) has used their mission of community-controlled transportation to partner with community based organizations on the launch and operations of E-Bike Libraries (EBLs) in Western New York (WNY) and beyond since 2021. For almost four years, the WNY EBLs have provided e-bikes at no cost to underserved communities in Buffalo and Niagara Falls. Participants used the e-bikes for commuting, recreational rides, community bike rides, running errands, and accessing essential services. This program significantly increased e-bike accessibility, with 71% of participants being first-time riders and 78% identifying as Black/African American. Challenges such as bike maintenance, battery charging logistics, and the need for suitable storage were addressed through partnerships with community-based organizations and adjustments to program logistics. Those lessons have been applied to additional EBLs in Pacoima, California and Carlisle, Pennsylvania, which have also been launched by SMI with a continued emphasis on the importance of community based approaches to sustainable transportation. All of these programs demonstrate the potential of e-bikes to provide an affordable, efficient, and fun transportation option, particularly for underserved communities. By leveraging community partnerships and focusing on accessibility and inclusivity, E-Bike Libraries can significantly contribute to sustainable transportation solutions and promote broader participation in the transportation electrification revolution.
The rapid expansion of artificial intelligence (AI) has triggered an unprecedented surge in electricity demand, with US data center energy use projected to double or triple 2023 levels by 2028. This exponential growth places strain on grid infrastructure, which can hinder timely construction of desired computing capacity. To bridge this supply-demand gap, utilities and AI developers are increasingly turning to demand flexibility, a strategy that incentivizes shifting or reducing power use during peak periods of grid stress. Data centers are uniquely equipped for flexible operations due to their digital workloads, built-in redundancy, and onsite energy assets. This article outlines four primary mechanisms to enable data center flexibility: computational load flexibility (shifting tasks temporally or geographically), flexible use of core facility infrastructure adjustments, energy storage utilization, and onsite electricity generation. To encourage adoption, utilities are deploying new tariff designs, including voluntary interruptible service riders, mandated flexibility requirements, and streamlined interconnection processes for flexible loads. For the highly capitalized and rapidly growing AI industry, the primary motivators for embracing these strategies are expediting facility interconnection, satisfying emerging regulatory mandates, and mitigating community resistance. While demand flexibility cannot substitute the long-term need for new bulk power generation, it serves as an essential, immediate solution for enabling near-term deployment. By transforming data centers from grid stressors into stabilizing assets, flexible operations can ensure reliable grid integration, ease market pressures, and support a resilient power system.
Curbs play a vital role in facilitating vehicle access and egress for individuals at airports. Inefficiently allocating this resource hinders airport accessibility and productivity, resulting in congestion, longer travel times, and increased pollution. As airport demand fluctuates throughout the day and grows over time, airports face intensified curbside pressure. Yet, curb management research is significantly less robust at airports than in urban areas. Given the unbalanced nature of airport demand—riders tend to arrive simultaneously at specific entrances at certain hours—Variable Message Sign (VMS) arises as a cost-effective technology to divert vehicles from congested to underutilized curbs. Still, VMS implementation faces a significant challenge. Historically, airports have managed VMS heuristically and by intuition rather than an evidence-based approach. This research investigates the impacts of implementing VMS on curb performance at airports. By considering different driver compliance rates (DCR), we aim to determine when the sign should be turned on and off to diverge traffic to avoid undesired externalities while enhancing curb performance. Using a validated agent-based microsimulation model, VISSIM, we analyzed the Seattle-Tacoma (SeaTac) Airport as a case study. We modeled sixteen VMS management scenarios and a baseline where the message sign is not displayed, diverging vehicles between the departures and arrivals access levels at four different moments (early morning, morning, afternoon, and late night). We quantified the effects of VMS using seven metrics, including curb productivity index (CPI), curb accessibility (CA), queue length, queue duration, delay, vehicle counts, and emissions. The results of each scenario were compared against the baseline using absolute and relative changes and Repeated Measures ANOVA. Overall, VMS improved curb performance and traffic conditions at the airport, reducing emissions by 14.8% to 8.9%. Moreover, significant reductions in queue length (1,150 ft to 100 ft) and duration (15 to 144 minutes) were observed in the sending link under all VMS policies. However, impacts on the receiving link varied based on congestion, with significant increases in queue duration (9.8 to 24 min) when congested but no substantial changes in free flow. Notably, diverging vehicles to congested links resulted in non-significant results, and activating late and deactivating late VMS affected curb productivity (-5.8% to -61.4%), curb accessibility (-16.5% to -25.8%), cumulative counts (-33.4% to -59.4%), and vehicle delay (95.98% to 594.3%). Activating VMS before congestion begins in the sending link and deactivating before a queue forms in the receiving link yield the most significant improvements: 8.1% to 10.1% in CPI, 9.4% to9.6% in CA, -29.3% to -77.9% in total delay, -11.6% to -13.9% in total emissions, and 101% to 103% in cumulative counts. As the analysis was made with a wide range of time periods, access levels, driver compliance rates, and scenarios, we believe our findings can provide valuable insights into how airports should manage VMS. Our work introduces a novel approach to the scientific airport literature, as some of our metrics were previously unexplored. Additionally, we propose a methodology that other airports can adopt to maximize their curb performance.
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Systematic study of astatine (At) sorption on extraction chromatography resins from nitric acid media has been performed at Texas A&M University. This work covers commercially available resins such as LN, TK400, SR, TRU, and UTEVA. Acquiring an understanding of At behavior in up to 4 M HNO 3 solutions is a key step to develop a rapid and reliable system for At separation and purification. The determined distribution coefficients are greater than 20 for all the resins studied, reaching 400 for TRU and UTEVA resins. The sorption uptake decreases in the order: TRU ≳ UTEVA >TK400 ≳ SR >LN. For each resin a thermodynamic model has been developed to suggest a possible mechanism of At sorption and corresponding sorption constants have been estimated. Literature data along with new results on bismuth (Bi) sorption by studied resins in nitric acid media have been reviewed and a mathematical model to describe its behavior has been suggested. A ratio of corresponding fit functions of At and Bi assigned to the same resin and acidity has been used to estimate separation factors of these elements. Furthermore, only the TRU resin is not suitable for efficient At isolation from Bi, while the other four resins demonstrate promising results.
The dual-axis duo-lateral (DADL) position-sensitive silicon detector was developed to obtain precise position and energy information for detected charged particles. The Forward Array Using Silicon Technology (FAUST) is currently equipped with 68 DADL detectors backed by CsI(Tl) scintillators for the study of charged particle correlations in heavy-ion collisions where precise position and energy information is essential. When conventional signal processing electronics were used for the DADL detectors, a position dependence of the measured energy as well as distortions in the calculated particle positions were observed. In previous work, waveforms from the detector after preamplification were studied to better understand the features that give rise to these distortions; therein, a waveform analysis technique was developed to improve the energy resolution and linearity in position reconstruction. However, the reading and writing of waveforms for an entire detector array limits data collection rates and adds significant burden in data storage and analysis speed. In this work, the integrators of a Struck SIS3316 ADC were utilized to process 228 Th source data to develop and optimize a new analysis method that captures the benefits of the waveform analysis technique while circumventing the waveform writing requirement. This integrator method – capable of 59 keV (FWHM) energy resolution – was used in the collection of 35 MeV/nucleon 28 Si + 12 C collision data using FAUST to investigate exotic decays of highly excited highly deformed nuclei. In this data, a position resolution of 0.4 mm (FWHM) was obtained for 25 MeV α-particles; for α-particles near this energy that originate from 8 Be ground state decays, a 8 Be ground state width of 30 keV (FWHM) was obtained. The impact of the energy-dependent DADL position resolution emergent from electronic noise on the quality of excited state measurement was modeled and compared to the experimental data.
The alpha emitter astatine-211 ( 211 At) is a promising candidate for cancer treatment based on Targeted Alpha (α) Therapy (TAT). A small number of facilities, distributed across the United States, are capable of accelerating α-particle beams to produce 211 At. However, challenges remain regarding strategic methods for shipping 211 At in a form adaptable to advanced radiochemistry reactions and other uses of the radioisotope. Purpose: Our method allows shipment of 211 At in various quantities in a form convenient for further radiochemistry. Procedures: For this study, a 3-octanone impregnated Amberchrom® CG300M resin bed in a column cartridge was used to separate 211 At from the bismuth matrix on site at the production accelerator (Texas A&M) in preparation for shipping. Aliquots of 6 M HNO 3 containing up to ≈2.22 GBq of 211 At from the dissolved target were successfully loaded and retained on columns. Exempt packages (<370 MBq) were shipped to a destination radiochemistry facility, University of Texas MD Anderson Cancer Center, in the form of a convenient air-dried column. Type A packages have been shipped overnight to University of Alabama at Birmingham. Main findings: Air-dried column hold times of various lengths did not inhibit simple and efficient recovery of 211 At. Solution eluted from the column was sufficiently high in specific activity to successfully radiolabel a model compound, 4-(4,4,5,5-tetramethyl-1,3,2-dioxaborolan-2-yl)aniline (1), with 211 At. The method to prepare and ship 211 At described in this manuscript has also been used to ship larger quantities of 211 At a greater distance to University of Alabama at Birmingham. Principal conclusions: The successful proof of this method paves the way for the distribution of 211 At from Texas A&M University to research institutions and clinical oncology centers in Texas and elsewhere. Finally, use of this simple method at other facilities has the potential increase the overall availability of 211 At for preclinical and clinical studies.
Terbium-149g (t 1/2 = 4.12 h) is of particular interest for targeted alpha therapy cancer treatment due to its ability to decay via both alpha and positron emission, making it a potential theranostic nuclide. Due to many challenges facing its production, there are limited facilities worldwide that have demonstrated the ability to produce this nuclide in quantities sufficient for medical research. Since the Cyclotron Institute at Texas A&M University is a specialized accelerator facility capable of accelerating a wide variety of ions, we are investigating production pathway options. One of the major challenges facing its production is the known co-production of the excited isomeric state, 149m Tb (t 1/2 = 4.1 min). However, this state does not decay to the ground state of 149g Tb, negating any potential contribution to its yield. Due to its short-half life, the cross section for the population of this state has never been measured. After calculating several potential reaction yields using predictive models, the reactions of 147–149 Sm( 6 Li,xn) 149 Tb were identified as candidates. Lithium-6 beams of varied energies between 45-65 MeV were impinged on enriched 147 Sm, 148 Sm, and 149 Sm targets at the Cyclotron Institute at Texas A&M University, and the reaction products were measured immediately following irradiation using high-purity germanium detectors, enabling detection of both 149m Tb and 149g Tb. Cross sections for all nuclides produced in sufficient activity in these reactions were also measured and reported here. We conclude that the population of 149m Tb is much preferred over population of the ground state for these 6 Li-induced reactions, and it is necessary to explore other options for 149g Tb production.
Astatine and bismuth sorption on several ion exchange resins from nitric acid media has been studied. This work covers commercially available resins Dowex 50 × 4, MP thiol, Dowex 1 × 8, and TEVA. One of the main advantages of using ion exchangers for astatine separation and purification is the absence of any organic media in the effluent in comparison with extraction chromatography resins. The behavior of the above-mentioned metals was investigated in up to 4 M HNO 3 solutions. The determined distribution coefficients are greater than 1 for all the resins studied, reaching 10 4 for MP thiol and TEVA resins. The interaction of nitric acid with an anion exchanger in Cl-form results in an exchange reaction, where AtO + chloro complexes can form. To understand the astatine behavior under these conditions, stability constants of AtOCl and AtOCl 2 – complexes have been reevaluated and discrepancy in the literature values has been eliminated. For each resin a thermodynamic model has been developed to suggest a possible mechanism of astatine sorption. Literature and new experimental data on bismuth sorption by studying resins in nitric acid media have been reviewed and a mathematical model to describe its behavior has been suggested. Furthermore, a ratio of corresponding fit functions of At and Bi assigned to the same resin and acidity has been used to estimate the separation factors of these elements.
The equation of state describes the emergent physical properties of matter. Experimental data is needed to help constrain the equation of state for nuclear matter. These constraints can help distinguish between an “asy-stiff” and an “asy-soft” equation of state, which has astrophysical implications. One path to help constrain the models is to analyze the nuclear caloric curve; some experiments have shown dependence on neutron excess, and may thus be sensitive to the asymmetry. A difference in the caloric curve based on the asymmetry of the reconstructed quasiprojectile (QP) had been observed using 70 Zn on 70 Zn at 35 MeV/nucleon taken with the NIMROD array. Antisymmetrized molecular dynamics calculations were performed for the same system and deexcited with gemini++. Both Gogny (asy-soft) and Gogny-as (asy-stiff) data sets were generated. The particles were then filtered based on detector geometric acceptance and thresholds. From the accepted particles, the excitation energy and temperature were calculated in the same way as for experimental data. Additionally, filter effects on the observed nuclear caloric curves were investigated. A tendency for the asy-stiff nuclear caloric curves to have higher temperatures than their asy-soft counterparts was observed for a number of probes. In addition, some probes may show sensitivity to the reconstructed composition of the QP, but this is inconclusive due to high statistical fluctuations and a large dependence on the exact method of event selection.