SEARCH · Engineering Papers

Results for “STARTING”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 955 records · Page 53

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Multiscale Physics of Atomic Nuclei from First Principles

Atomic nuclei exhibit multiple energy scales ranging from hundreds of MeV in binding energies to fractions of an MeV for low-lying collective excitations. As the limits of nuclear binding are approached near the neutron and proton drip lines, traditional shell structure starts to melt with an onset of deformation and an emergence of coexisting shapes. It is a long-standing challenge to describe this multiscale physics starting from nuclear forces with roots in quantum chromodynamics. Here, we achieve this within a unified and nonperturbative quantum many-body framework that captures both short- and long-range correlations starting from modern nucleon-nucleon and three-nucleon forces from chiral effective field theory. The short-range (dynamic) correlations which account for the bulk of the binding energy are included within a symmetry-breaking framework, while long-range (static) correlations (and fine details about the collective structure) are included by employing symmetry projection techniques. Our calculations accurately reproduce—within theoretical error bars—available experimental data for low-lying collective states and the electromagnetic quadrupole transitions in 20−30 Ne. In addition, we reveal coexisting spherical and deformed shapes in 30 Ne, which indicates the breakdown of the magic neutron number 𝑁 = 20 as the key nucleus 28 O is approached, and we predict that the drip line nuclei 32,34 Ne are strongly deformed and collective. By developing reduced-order models for symmetry-projected states, we perform a global sensitivity analysis and find that the subleading singlet 𝑆-wave contact and a pion-nucleon coupling strongly impact nuclear deformation in chiral effective field theory. The techniques developed in this work clarify how microscopic nuclear forces generate the multiscale physics of nuclei spanning collective phenomena as well as short-range correlations and allow one to capture emergent and dynamical phenomena in finite fermion systems such as atom clusters, molecules, and atomic nuclei.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2026

Structure-aware Initialization via Numerical Continuation and Informed Priors

Scientific machine learning (SciML) often operates in ill-conditioned, weakly identifiable regimes due to limited data or indirect observations. In such settings, optimization and inference are highly sensitive to the starting point, making initialization--often under-reported--a consequential degree of freedom. Random initialization is not a neutral default as it induces an implicit prior over candidate solutions and can systematically bias the result, producing large run-to-run variability. Here, we formalize this view by treating initialization as a hidden confounder in SciML and develop a unifying theory for structure-aware initialization via numerical continuation, constructing warm starts from related problem instances. Across representative tasks, including physics-informed neural networks, maximum likelihood estimation, and variational inference, warm starts have been shown to consistently reduce optimization effort and improve reliability.

Data integrity↗

DOE OSTI2023

Impact of Detailed Parameter Modeling of Open-Cycle Gas Turbines on Production Cost Simulation: Preprint

Flexible resources are increasingly important as variable renewable energy deployment in the power system increases. Although many systems are transitioning away from fossil fuels, open-cycle gas turbines are likely to play an important balancing role for some time, thus requiring accurate modeling of their operational parameters. This paper explores the impact of detailed representation of three operational parameters - start- up costs, run-up rates, and forced outage rates - in the production cost model of a system as it adopts higher levels of wind and solar. Using PLEXOS simulations of the NREL-118 bus test system, the study examines how more detailed parameter modeling affects outcomes such as the number of start-ups and shutdowns, ramping and total generation costs for open-cycle gas turbines, as renewable energy levels increase. The results suggest the value of detailed parameter modeling and continued research on combustion turbines' ability to provide flexibility.

economic dispatch↗

DOE OSTI2026

Safe Deep Reinforcement Learning for Robust Frequency and Voltage-Constrained Networked Microgrid Restoration

Here, this paper proposes a safe soft actor-critic reinforcement learning (RL) algorithm–based controller for networked microgrid restoration. It formulates the post black-start start as a finite-horizon constrained Markov decision process. The RL agent co-optimizes real and reactive power set-points for both grid-forming and grid-following inverters under explicit voltage and frequency constraints, while enforcing proper power sharing via the Mean Active Power Sharing Index (MPSI) and Mean Reactive Power Sharing Index (MQSI). Numerical results obtained on the IEEE 123-bus distribution system show that the proposed method achieves a mean voltage build-up time of 0.01 s without breaching the 5% sharing-violation budget under various load scenarios, considering MPSI and MQSI indices. These findings demonstrate that the proposed method yields fast and safe black-start schedules without resorting to heuristic penalties.

Selim, Alaa [Dartmouth College, Hanover, NH (Unite↗

DOE OSTI2018

Phase transitions of α-quartz at elevated temperatures under dynamic compression using a membrane-driven diamond anvil cell: Clues to impact cratering?

Coesite and stishovite are high-pressure silica polymorphs known to have been formed at several terrestrial impact structures. They have been used to assess pressure and temperature conditions that deviate from equilibrium formation conditions. Here in this paper, we investigate the effects of nonhydrostatic, dynamic stresses on the formation of high-pressure polymorphs and the amorphization of α-quartz at elevated temperatures. The obtained disequilibrium states are compared with those predicted by phase diagrams derived from static experiments under equilibrium conditions. We analyzed phase transformations starting with α-quartz in situ under dynamic loading utilizing a membrane-driven diamond anvil cell. Using synchrotron powder X-ray diffraction, the phase transitions of SiO 2 are identified up to 77.2 GPa and temperatures of 1160 K at compression rates ranging between 0.10 and 0.37 GPa s -1 . Coesite starts forming above 760 K in the pressure range between 2 and 11 GPa. At 1000 K, coesite starts to transform to stishovite. This phase transition is not completed at 1160 K in the same pressure range. Therefore, the temperature initiates the phase transition from α-quartz to coesite, and the transition from coesite to stishovite. Below 1000 K and during compression, α-quartz becomes amorphous and partially converts to stishovite. This phase transition occurs between 25 and 35 GPa. Above 1000 K, no amorphization of α-quartz is observed. High temperature experiments reveal the strong thermal dependence of the formation of coesite and stishovite under nonhydrostatic and disequilibrium conditions.

58 GEOSCIENCES↗

DOE OSTI2019

Predicting Cycle-to-Cycle Variation With Concurrent Cycles in a Gasoline Direct Injected Engine With Large Eddy Simulations

High cycle-to-cycle variation (CCV) is detrimental to engine performance, as it leads to poor combustion and high noise and vibration. In this work, CCV in a gasoline engine is studied using large eddy simulation (LES). The engine chosen as the basis of this work is a single-cylinder gasoline direct injection (GDI) research engine. Two stoichiometric part-load engine operating points (6 BMEP, 2000 RPM) were evaluated: a non-dilute (0% EGR) case and a dilute (18% EGR) case. The experimental data for both operating conditions had 500 cycles. The measured CCV in IMEP was 1.40% for the non-dilute case and 7.78% for the dilute case. To estimate CCV from simulation, perturbed concurrent cycles of engine simulations were compared to consecutively obtained engine cycles. The motivation behind this is that running consecutive cycles to estimate CCV is quite time-consuming. For example, running 100 consecutive cycles requires 2–3 months (on a typical cluster), however, by running concurrently one can potentially run all 100 cycles at the same time and reduce the overall turnaround time for 100 cycles to the time taken for a single cycle (2 days). The goal of this paper is to statistically determine if concurrent cycles, with a perturbation applied to each individual cycle at the start, can be representative of consecutively obtained cycles and accurately estimate CCV. 100 cycles were run for each case to obtain statistically valid results. The concurrent cycles began at different timings before the combustion event, with the motivation to identify the closest time before spark to minimize the run time. Only a single combustion cycle was run for each concurrent case. The calculated standard deviation of peak pressure and coefficient of variance (COV) of indicated mean effective pressure (IMEP) were compared between the consecutive and concurrent methods to quantify CCV. It was found that the concurrent method could be used to predict CCV with either a velocity or numerical perturbation. Here, a large and small velocity perturbation were compared and both produced correct predictions, implying that the type of perturbation is not important to yield a valid realization. Starting the simulation too close to the combustion event, at intake valve close (IVC) or at spark timing, under-predicted the CCV. When concurrent simulations were initiated during or before the intake even, at start of injection (SOI) or earlier, distinct and valid realizations were obtained to accurately predict CCV for both operating points. By simulating CCV with concurrent cycles, the required wall clock time can be reduced from 2–3 months to 1–2 days. Additionally, the required core-hours can be reduced up to 41%, since only a portion of each cycle needs to be simulated.

42 ENGINEERING↗

DOE OSTI2014

Comparison of two methods for minimizing the effect of delayed charge on the dose delivered with a synchrotron based discrete spot scanning proton beam

Purpose: Delayed charge is a small amount of charge that is delivered to the patient after the planned irradiation is halted, which may degrade the quality of the treatment by delivering unwarranted dose to the patient. This study compares two methods for minimizing the effect of delayed charge on the dose delivered with a synchrotron based discrete spot scanning proton beam. Methods: The delivery of several treatment plans was simulated by applying a normally distributed value of delayed charge, with a mean of 0.001(SD 0.00025) MU, to each spot. Two correction methods were used to account for the delayed charge. Method one (CM1), which is in active clinical use, accounts for the delayed charge by adjusting the MU of the current spot based on the cumulative MU. Method two (CM2) in addition reduces the planned MU by a predicted value. Every fraction of a treatment was simulated using each method and then recomputed in the treatment planning system. The dose difference between the original plan and the sum of the simulated fractions was evaluated. Both methods were tested in a water phantom with a single beam and simple target geometry. Two separate phantom tests were performed. In one test the dose per fraction was varied from 0.5 to 2 Gy using 25 fractions per plan. In the other test the number fractions were varied from 1 to 25, using 2 Gy per fraction. Three patient plans were used to determine the effect of delayed charge on the delivered dose under realistic clinical conditions. The order of spot delivery using CM1 was investigated by randomly selecting the starting spot for each layer, and by alternating per layer the starting spot from first to last. Only discrete spot scanning was considered in this study. Results: Using the phantom setup and varying the dose per fraction, the maximum dose difference for each plan of 25 fractions was 0.37–0.39 Gy and 0.03–0.05 Gy for CM1 and CM2, respectively. While varying the total number of fractions, the maximum dose difference increased at a rate of 0.015 Gy and 0.0018 Gy per fraction for CM1 and CM2, respectively. For CM1, the largest dose difference was found at the location of the first spot in each energy layer, whereas for CM2 the difference in dose was small and showed no dependence on location. For CM1, all of the fields in the patient plans had an area where their excess dose overlapped. No such correlation was found when using CM2. Randomly selecting the starting spot reduces the maximum dose difference from 0.708 to 0.15 Gy. Alternating between first and last spot reduces the maximum dose difference from 0.708 to 0.37 Gy. In the patient plans the excess dose scaled linearly at 0.014 Gy per field per fraction for CM1 and standard delivery order. Conclusions: The predictive model CM2 is superior to a cumulative irradiation model CM1 for minimizing the effects of delayed charge, particularly when considering maximal dose discrepancies and the potential for unplanned hot-spots. This study shows that the dose discrepancy potentially scales at 0.014 Gy per field per fraction for CM1.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

SU-E-J-181: Magnetic Resonance Image-Guided Radiation Therapy Workflow: Initial Clinical Experience

Purpose: The aims of this work are to describe the workflow and initial clinical experience treating patients with an MRI-guided radiotherapy (MRIGRT) system. Methods: Patient treatments with a novel MR-IGRT system started at our institution in mid-January. The system consists of an on-board 0.35-T MRI, with IMRT-capable delivery via doubly-focused MLCs on three {sup 60} Co heads. In addition to volumetric MR-imaging, real-time planar imaging is performed during treatment. So far, eleven patients started treatment (six finished), ranging from bladder to lung SBRT. While the system is capable of online adaptive radiotherapy and gating, a conventional workflow was used to start, consisting of volumetric imaging for patient setup using visible tumor, evaluation of tumor motion outside of PTV on cine images, and real-time imaging. Workflow times were collected and evaluated to increase efficiency and evaluate feasibility of adding the adaptive and gating features while maintaining a reasonable patient throughput. Results: For the first month, physicians attended every fraction to provide guidance on identifying the tumor and an acceptable level of positioning and anatomical deviation. Average total treatment times (including setup) were reduced from 55 to 45 min after physician presence was no longer required and the therapists had learned to align patients based on soft-tissue imaging. Presently, the source strengths were at half maximum (7.7K Ci each), therefore beam-on times will be reduced after source replacement. Current patient load is 10 per day, with increase to 25 anticipated in the near future. Conclusion: On-board, real-time MRI-guided RT has been incorporated into clinical use. Treatment times were kept to reasonable lengths while including volumetric imaging, previews of tumor movement, and physician evaluation. Workflow and timing is being continuously evaluated to increase efficiency. In near future, adaptive and gating capabilities of the system will be implemented.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

WE-D-BRE-04: Modeling Optimal Concurrent Chemotherapy Schedules

Purpose: Concurrent chemo-radiation therapy (CCRT) has become a more common cancer treatment option with a better tumor control rate for several tumor sites, including head and neck and lung cancer. In this work, possible optimal chemotherapy schedules were investigated by implementing chemotherapy cell-kill into a tumor response model of RT. Methods: The chemotherapy effect has been added into a published model (Jeong et al., PMB (2013) 58:4897), in which the tumor response to RT can be simulated with the effects of hypoxia and proliferation. Based on the two-compartment pharmacokinetic model, the temporal concentration of chemotherapy agent was estimated. Log cell-kill was assumed and the cell-kill constant was estimated from the observed increase in local control due to concurrent chemotherapy. For a simplified two cycle CCRT regime, several different starting times and intervals were simulated with conventional RT regime (2Gy/fx, 5fx/wk). The effectiveness of CCRT was evaluated in terms of reduction in radiation dose required for 50% of control to find the optimal chemotherapy schedule. Results: Assuming the typical slope of dose response curve (γ50=2), the observed 10% increase in local control rate was evaluated to be equivalent to an extra RT dose of about 4 Gy, from which the cell-kill rate of chemotherapy was derived to be about 0.35. Best response was obtained when chemotherapy was started at about 3 weeks after RT began. As the interval between two cycles decreases, the efficacy of chemotherapy increases with broader range of optimal starting times. Conclusion: The effect of chemotherapy has been implemented into the resource-conservation tumor response model to investigate CCRT. The results suggest that the concurrent chemotherapy might be more effective when delayed for about 3 weeks, due to lower tumor burden and a larger fraction of proliferating cells after reoxygenation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Poster — Thur Eve — 30: 4D VMAT dose calculation methodology to investigate the interplay effect: experimental validation using TrueBeam Developer Mode and Gafchromic film

The interplay effect between the tumor motion and the radiation beam modulation during a VMAT treatment delivery alters the delivered dose distribution from the planned one. This work present and validate a method to accurately calculate the dose distribution in 4D taking into account the tumor motion, the field modulation and the treatment starting phase. A QUASAR™ respiratory motion phantom was 4D scanned with motion amplitude of 3 cm and with a 3 second period. A static scan was also acquired with the lung insert and the tumor contained in it centered. A VMAT plan with a 6XFFF beam was created on the averaged CT and delivered on a Varian TrueBeam and the trajectory log file was saved. From the trajectory log file 10 VMAT plans (one for each breathing phase) and a developer mode XML file were created. For the 10 VMAT plans, the tumor motion was modeled by moving the isocentre on the static scan, the plans were re-calculated and summed in the treatment planning system. In the developer mode, the tumor motion was simulated by moving the couch dynamically during the treatment. Gafchromic films were placed in the QUASAR phantom static and irradiated using the developer mode. Different treatment starting phase were investigated (no phase shift, maximum inhalation and maximum exhalation). Calculated and measured isodose lines and profiles are in very good agreement. For each starting phase, the dose distribution exhibit significant differences but are accurately calculated with the methodology presented in this work.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Poster — Thur Eve — 03: Application of the non-negative matrix factorization technique to [{sup 11}C]-DTBZ dynamic PET data for the early detection of Parkinson's disease

In this work, a class of non-negative matrix factorization (NMF) technique known as alternating non-negative least squares, combined with the projected gradient method, is used to analyze twenty-five [{sup 11}C]-DTBZ dynamic PET/CT brain data. For each subject, a two-factor model is assumed and two factors representing the striatum (factor 1) and the non-striatum (factor 2) tissues are extracted using the proposed NMF technique and commercially available factor analysis software “Pixies”. The extracted factor 1 and 2 curves represent the binding site of the radiotracer and describe the uptake and clearance of the radiotracer by soft tissues in the brain, respectively. The proposed NMF technique uses prior information about the dynamic data to obtain sample time-activity curves representing the striatum and the non-striatum tissues. These curves are then used for “warm” starting the optimization. Factor solutions from the two methods are compared graphically and quantitatively. In healthy subjects, radiotracer uptake by factors 1 and 2 are approximately 35–40% and 60–65%, respectively. The solutions are also used to develop a factor-based metric for the detection of early, untreated Parkinson's disease. The metric stratifies healthy subjects from suspected Parkinson's patients (based on the graphical method). The analysis shows that both techniques produce comparable results with similar computational time. The “semi-automatic” approach used by the NMF technique allows clinicians to manually set a starting condition for “warm” starting the optimization in order to facilitate control and efficient interaction with the data.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-126: An Online Replanning Method for FFF Beams Without Couch Shift

Purpose: In a situation that couch shift for patient positioning is not preferred or prohibited (e.g., MR-Linac), segment aperture morphing (SAM) can address target dislocation and deformation. For IMRT/VMAT with flattening filter free (FFF) beams, however, SAM method would lead to an adverse translational dose effect due to the beam unflattening. Here we propose a new 2-step process to address both the translational effect of FFF beams and the target deformation. Methods: The replanning method consists of an offline and an online steps. The offline step is to create a series of pre-shifted plans (PSP) obtained by a so called “warm start” optimization (starting optimization from the original plan, rather from scratch) at a series of isocenter shifts with fixed distance (e.g. 2 cm, at x,y,z = 2,0,0 ; 2,2,0 ; 0,2,0; …;− 2,0,0). The PSPs all have the same number of segments with very similar shapes, since the warm-start optimization only adjusts the MLC positions instead of regenerating them. In the online step, a new plan is obtained by linearly interpolating the MLC positions and the monitor units of the closest PSPs for the shift determined from the image of the day. This two-step process is completely automated, and instantaneously fast (no optimization or dose calculation needed). The previously-developed SAM algorithm is then applied for daily deformation. We tested the method on sample prostate and pancreas cases. Results: The two-step interpolation method can account for the adverse dose effects from FFF beams, while SAM corrects for the target deformation. The whole process takes the same time as the previously reported SAM process (5–10 min). Conclusion: The new two-step method plus SAM can address both the translation effects of FFF beams and target deformation, and can be executed in full automation requiring no additional time from the SAM process. This research was supported by Elekta inc. (Crawley, UK)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Early detection of chemotherapy-refractory patients by monitoring textural alterations in diffuse optical spectroscopic images

Purpose: Changes in textural characteristics of diffuse optical spectroscopic (DOS) functional images, accompanied by alterations in their mean values, are demonstrated here for the first time as early surrogates of ultimate treatment response in locally advanced breast cancer (LABC) patients receiving neoadjuvant chemotherapy (NAC). NAC, as a standard component of treatment for LABC patient, induces measurable heterogeneous changes in tumor metabolism which were evaluated using DOS-based metabolic maps. This study characterizes such inhomogeneous nature of response development, by determining alterations in textural properties of DOS images apparent at early stages of therapy, followed later by gross changes in mean values of these functional metabolic maps. Methods: Twelve LABC patients undergoing NAC were scanned before and at four times after treatment initiation, and tomographic DOS images were reconstructed at each time. Ultimate responses of patients were determined clinically and pathologically, based on a reduction in tumor size and assessment of residual tumor cellularity. The mean-value parameters and textural features were extracted from volumetric DOS images for several functional and metabolic parameters prior to the treatment initiation. Changes in these DOS-based biomarkers were also monitored over the course of treatment. The measured biomarkers were applied to differentiate patient responses noninvasively and compared to clinical and pathologic responses. Results: Responding and nonresponding patients demonstrated different changes in DOS-based textural and mean-value parameters during chemotherapy. Whereas none of the biomarkers measured prior the start of therapy demonstrated a significant difference between the two patient populations, statistically significant differences were observed at week one after treatment initiation using the relative change in contrast/homogeneity of seven functional maps (0.001 < p < 0.049), and mean value of water content in tissue (p = 0.010). The cross-validated sensitivity and specificity of these parameters at week one of therapy ranged between 80%–100% and 67%–100%, respectively. Higher levels of statistically significant differences were exhibited at week four after start of treatment, with cross-validated sensitivities and specificities ranging between 80% and 100% for three textural and three mean-value parameters. The combination of the textural and mean-value parameters in a “hybrid” profile could better separate the two patient populations early on during a course of treatment, with cross-validated sensitivities and specificities of up to 100% (p = 0.001). Conclusions: The results of this study suggest that alterations in textural characteristics of DOS images, in conjunction with changes in their mean values, can classify noninvasively the ultimate clinical and pathologic response of LABC patients to chemotherapy, as early as one week after start of their treatment. This provides a basis for using DOS imaging as a tool for therapy personalization.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-P-03: Management of Time to Treatment Inititation: Case for An Electronic Whiteboard

Purpose: To determine if data mining of an electronic whiteboard improves the management of the Time to Treatment Initiation (TTI) in radiation oncology. Methods: An electronic whiteboard designed to help in managing the planning workflow and improves communication regarding patient planning progress was used to record the dates at which each phase of the planning process began or completed. These are CT Sim date, Plan Start, Physician Review, Physicist Review, Approval for Treatment Delivery, Setup or Verification of Simulation. Results: During clinical implementation, the electronic whiteboard was able to fulfill its primary objective of providing a transparent account of the planning progress of each patient. Peer pressure also meant that individual tasks, such as contouring, were easily brought to the attention of the responsible party and prioritized accordingly. Data mining to analyze the electronic whiteboard per patient (figure 1), per diagnosis (figure 2), per treatment modality (figure 3), per physician (figure 4), per planner (figure 5), etc., added another sophisticated tool in the management of Time to Treatment Initiation without compromising quality of the plans being generated. A longer than necessary time between CT Sim and Plan Start can be discussed among the members of the treatment team as an indication of inadequate/outdated CT Simulator, Contouring Tools, Image Fusion Tools, Other Imaging Studies (MRI, PET/CT) performed, etc. The same for the Plan Start to Physician Review where an extended time than expected may be due unrealistic planning goals, limited planning system features, etc. Conclusion: An Electronic Whiteboard in radiation oncology is not only helping with organizing planning workflow, it is also a potent tool that can be used to reduce the Time to Treatment Initiation by providing the clinic with hard data about the duration of each phase treatment planning as a function of different variable affecting the planning process. The work is supported by the Global Medical Physics Institute.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Cell Cycle-Dependent Recruitment of FtsN to the Divisome in Escherichia coli

Cell division in Escherichia coli starts with the formation of an FtsZ protofilament network at midcell, the Z ring. However, only after a considerable lag period does the cell start to form a midcell constriction. The onset of constriction depends upon the arrival of so-called late divisome proteins, among which, FtsN is the last essential one. The timing and dependency of FtsN arrival to the divisome, along with genetic evidence, suggests it triggers cell division. In this study, we used high-throughput fluorescence microscopy to determine the arrival of FtsN and the early divisome protein ZapA to midcell at a single-cell level during the cell cycle. Our data show while the recruitment of ZapA/FtsZ is gradual in the cell cycle, recruitment of FtsN is rapid and begins at about the onset of constriction. At this time, the fraction of ZapA/FtsZ in the Z ring approaches its peak value. We also find a second increase in FtsN recruitment to the divisome, which begins once the amount of ZapA/FtsZ at midcell starts decreasing. Increasing hypermorphic FtsA* (FtsA R286W), but not FtsA, accelerates FtsN recruitment but not constriction. This finding is consistent with FtsA* recruiting FtsN with some other divisome component being rate-limiting for constriction under these conditions. Finally, our data support the recently proposed idea that ZapA/FtsZ and FtsN are part of physically separate complexes in midcell throughout the whole septation process.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Synthesis of the Ti{sub 2}AlC MAX Phase with a Reduction Step via Combustion of a TiO{sub 2} + Mg + Al + C Mixture

Technologically viable principles have been developed for the preparation of the MAX phase Ti{sub 2}AlC by self-propagating high-temperature synthesis (SHS) with a reduction step, using titanium dioxide. We have studied the influence of synthesis conditions (starting-mixture composition and ratio of reactants) on the composition, structure, and particle size of Ti{sub 2}AlC powders. The results demonstrate that an excess of magnesium in the starting mixture leads to a decrease in the percentage of MgAl{sub 2}O{sub 4} (spinel), and carbon deficiency in the starting mixture reduces the percentage of titanium carbide in the final product. The Ti{sub 2}AlC powders prepared by SHS consist of agglomerates of layered particles differing in size: from coarse (several microns) to ultrafine and nanometer-sized particles. The composition of the powders was confirmed by chemical analysis, microstructural examination, and X-ray diffraction.

36 MATERIALS SCIENCE↗

DOE OSTI2013

Ice-Crystallization Kinetics in the Catalyst Layer of a Proton-Exchange-Membrane Fuel Cell

Nucleation and growth of ice in the catalyst layer of a proton-exchange-membrane fuel cell (PEMFC) are investigated using isothermal differential scanning calorimetry and isothermal galvanostatic cold-starts. Isothermal ice-crystallization rates and ice-nucleation rates are obtained from heat-flow and induction-time measurements at temperatures between 240 and 273 K for four commercial carbon-support materials with varying ionomer fraction and platinum loading. Measured induction times follow expected trends from classical nucleation theory and reveal that the carbon-support material and ionomer fraction strongly impact the onset of ice crystallization. Conversely, dispersed platinum particles play little role in ice crystallization. Following our previous approach, a nonlinear ice-crystallization rate expression is obtained from Johnson-Mehl-Avrami-Kolmogorov (JMAK) theory. A validated rate expression is now available for predicting ice crystallization within water-saturated catalyst layers. Using a simplified PEMFC isothermal cold-start continuum model, we compare cell-failure time predicted using the newly obtained rate expression to that predicted using a traditional thermodynamic-based approach. From this comparison, we identify conditions under which including ice-crystallization kinetics is critical and elucidate the impact of freezing kinetics on low-temperature PEMFC operation. The numerical model illustrates that cell-failure time increases with increasing temperature due to a longer required time for ice nucleation. Hence, ice-crystallization kinetics is critical when induction times are long (i.e., in the "nucleation-limited" regime for T > 263 K). Cell-failure times predicted using ice-freezing kinetics are in good agreement with the isothermal cold-starts, which also exhibit long and distributed cell-failure times for T > 263 K. These findings demonstrate a significant departure from cell-failure times predicted using the thermodynamic-based approach.

Dursch, T. J.↗

DOE OSTI2025

Ocpp 2.0.1. Interim Kpi Calculator

The project is split into four pieces. The first is a raw OCPP log parser. The second is a file splitter. The third is a message parser. The final piece is the Interim KPI calculator. The OCPP log parser was created from two different formats of raw OCPP 2.0.1 data. Its intended purpose is to extract device IDs and OCPP event messages from nontabular text logs. The parser looks for specific substrings in the logs to identify which of the two "standards" it should select from. The KPI generator does not perform any of its calculations in parallel. Instead, we opt for a naive batching approach. The splitter takes the file generated from the parser and creates many smaller files for each of the device IDs in the dataset. This allows the pandas queries in the log formatter to be iterate over a significantly smaller slice of data, increasing performance significantly. The message parser step takes messages from each of the files (containing distinct device IDs) and breaks the message out into pieces. The final result is a file with different columns specifying different attributes of the JSON message. The file is an aggregation of all different devices. This is the most complex portion of the code. The KPI calculator takes the parsed messages, as a single file, and calculates the KPI from that data. An excel file is produced with four sheets. These contain the metrics for Session Success, Charge Start Success, Charge End Success, and Charge Start Time. It includes the metrics for the different equations in the Interim KPI Implementation Guide as well as a weighted sum of the different equations for each KPI (excluding Charge End Success and Charge Start Time).

Quinn, Casey↗