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At least 37 records · Page 2

Learning electric vehicle driver range anxiety with an initial state of charge-oriented gradient boosting approach

This manuscript focuses on the modeling of electric vehicle (EV) driver’s range anxiety, a fear that a vehicle does not have sufficient range, or state of charge (SOC) of the battery pack, to reach its destination and would strand its occupants. Despite numerous research studies on the modeling of charging behaviors, modeling efforts to understand at what battery percentages do EV drivers charge their vehicles, and what are the associated contributing factors, are rather limited. To this end, an ensemble learning model based on gradient boosting is developed. The model sequentially fits new predictors to new residuals of the previous prediction and, then, minimizes the loss when adding the latest prediction. A total of 18 features are defined and extracted from the multisource data, which cover information on driver, vehicles, stations, traffic conditions, as well as spatial-temporal context information of the charging events. The analyzed dataset includes 4.5-year’s charging event log data from 3,096 users and 468 public charging stations in Kansas City Missouri, and the macroscopic travel demand model maintained by the metropolitan planning organization. Here, the result shows the proposed model achieved a satisfactory result with a R square value of 0.54 and root mean square error of 0.14, both better than multiple linear regression model and random forest model. To reduce range anxiety, it is suggested that the priorities of deploying new charging facilities should be given to the areas with higher daily traffic prediction, with more conservative EV users or that are further from residential areas.

33 ADVANCED PROPULSION SYSTEMS↗

Initial Process Planning of a Hybrid Multi-Tasking Platform

Abstract Applications of hybrid technology are expanding from refurbishment and repair to low quantity, specialty part production, which are staple characteristics in medical implant, energy, and aerospace industry sectors, among others. This expansion has led to the development of the Mazak VC-500A/5X AM HWD, a wire fed laser cladding unit equipped with a standard 5 axis CNC. This unit is capable of building near net geometry of complex medium to large parts within a profitable timeframe, due to its comparatively high rate of deposition to that of a powder fed hybrid system. In this study, deposition and machining capabilities of the VC-500A/5X AM HWD are assessed through the production of three different test geometries by different process plans. Production of these test geometries is supported by an open loop sensor package primarily for monitoring machine health, data collection, and machine operator aid. The viability of extended deposition followed by machining is evaluated against a more cyclical strategy of reoccurring deposition and machining operations. Lastly, common defects in as-built geometries are evaluated and addressed through revisions to original process plans and toolpaths, indicating the need for continued innovation in hybrid manufacturing specific CAM/CAD software, as well as closed loop machine monitoring and quality control.

DeWitte, Lisa N.↗

Design Initiative for a 10 TeV pCM Wakefield Collider

This document outlines a community-driven Design Study for a 10 TeV pCM Wakefield Accelerator Collider. The 2020 ESPP Report emphasized the need for Advanced Accelerator R&D, and the 2023 P5 Report calls for the ``delivery of an end-to-end design concept, including cost scales, with self-consistent parameters throughout." This Design Study leverages recent experimental and theoretical progress resulting from a global R&D program in order to deliver a unified, 10 TeV Wakefield Collider concept. Wakefield Accelerators provide ultra-high accelerating gradients which enables an upgrade path that will extend the reach of Linear Colliders beyond the electroweak scale. Here, we describe the organization of the Design Study including timeline and deliverables, and we detail the requirements and challenges on the path to a 10 TeV Wakefield Collider.

43 PARTICLE ACCELERATORS↗

Newton-Raphson AC Power Flow Convergence Based on Deep Learning Initialization and Homotopy Continuation

Power flow forms the basis of many power system studies. With the increased penetration of renewable energy, grid planners tend to perform multiple power flow simulations under various operating conditions and not just selected snapshots at peak or light load conditions. Getting a converged AC power flow (ACPF) case remains a significant challenge for grid planners especially in large power grid networks. This paper proposes a two-stage approach to improve Newton-Raphson ACPF convergence and was applied to a 6102 bus Electric Reliability Council of Texas (ERCOT) system. The first stage utilizes a deep learning-based initializer with data re-training. Here a deep neural network (DNN) initializer is developed to provide better initial voltage magnitude and angle guesses to aid in power flow convergence. This is because Newton-Raphson ACPF is quite sensitive to the initial conditions and bad initialization could lead to divergence. The DNN initializer includes a data re-training framework that improves the initializer's performance when faced with limited training data. The DNN initializer successfully solved 3,285 cases out of 3,899 non-converging dispatch and performed better than random forest and DC power flow initialization methods. ACPF cases not solved in this first stage are then passed through a hot-starting algorithm based on homotopy continuation with switched shunt control. The hot-starting algorithm successfully converged 416 cases out of the remaining 614 non-converging ACPF dispatch. In conclusion, the combined two-stage approach achieved a 94.9% success rate, by converging a total of 3,701 cases out of the initial 3,899 unsolved cases.

Deep learning↗

Effect of Initiator Density, Catalyst Concentration, and Surface Curvature on the Uniformity of Polymers Grafted from Spherical Nanoparticles

Polymer-grafted nanoparticles (PGNPs) are versatile hybrid materials whose properties critically depend on brush dimensions, uniformity, and grafting density. Herein, we systematically investigated how initiator density, catalyst concentration, and nanoparticle curvature govern the growth of poly(methyl methacrylate) (PMMA) brushes grafted from spherical SiO 2 nanoparticles via surface-initiated activators regenerated by electron transfer atom transfer radical polymerization (SI-ARGET ATRP). By tuning the initiator density through a combination of “active” and “dummy” silane initiators anchored on the nanoparticles’ surface and controlling the catalyst concentration, we reveal that increased initiator crowding and smaller surface curvature amplify steric hindrance, leading to decreased initiation efficiency and broader molecular weight distributions. Correlation with the corresponding unattached chains by ARGET ATRP suggests the presence of permanently inaccessible (“buried”) initiation sites, which are a characteristic of surface-grafted systems. At sufficient Cu catalyst concentrations, uniform brush growth is attained across different initiator densities, whereas decreased catalyst concentrations accentuate nonconcurrent initiation and propagation. These findings provide mechanistic insights into the interplay of initiator density, catalyst concentration, and surface curvature, offering design principles for tailoring the PGNP architecture. These results can guide the structural engineering of densely grafted surfaces, including nanoparticles and flat substrates, for applications in nanocomposites, photonics, and functional coatings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Crucial roles of eastward propagating environments in the summer MCS initiation over the U.S. Great Plains

Mesoscale convective systems (MCSs) frequently occur over the U.S. Great Plains during summer. An analysis using self-organizing map is conducted to identify four types of summer MCS initiation environments during 2004-2017. The first two types feature favorable large-scale environments at both upper and low levels, while Type-3 has favorable lower-level and surface conditions but unfavorable upper-level circulation, and Type-4 features the most unfavorable large-scale environments for MCS initiation. Despite the unfavorable large-scale environment, the convection-centered environments in Type-4 are favorable for MCS initiation and similar to the first two types, suggesting a role of sub-synoptic disturbances as an MCS precursor. All four types of the MCS initiation delineate a clear eastward propagating feature in many fields, such as upper-level potential vorticity/geopotential height, surface pressure and surface equivalent potential temperature, upstream up to 25°-longitude west of and ~36 hours before the MCS initiation. The propagating environments and local, non-propagating low-level moisture are found to be important in MCS initiation at the foothill of the Rocky Mountains, but over the central Great Plains, it is the coupling of dynamical and moisture anomalies associated with propagating waves that results in the MCS initiation. By tracking MCSs and mid-tropospheric perturbations (MPs), a type of sub-synoptic disturbances with Rocky Mountains origin, ~30% of MPs is associated with MCS initiation, mostly in Type-4. Although MPs are related to a small fraction of MCS initiation, MCSs that are associated with MPs tend to produce more rainfall in a larger area with a stronger convective intensity, suggesting MPs to be a source of intense MCSs in summer.

Song, Fengfei↗

Effect of Initial Water Saturation on The Performance of Fracturing Fluids With and Without Polyallylamine under Simulated EGS Conditions

Objectives/Scope: StimuFrac (US Patents 9,873,828 B2 and 9,447,315 B2), a CO2-reactive polymer aqueous solution [polyallylamine (PAA) 1wt% in water] combined with CO2, can be used as a less water-intensive fracturing fluid for enhanced geothermal systems (EGS). Our previous results show that in hot dry rock (HDR), PAA/CO2 fracturing fluids outperformed other fluids such as water, CO2, and CO2/water in generating large fractures with less fluid consumed. The objective of this work is to study the effect of initial water saturation of rock on the performance of StimuFrac fluid in ½ foot cubic rock samples and under representative EGS pressure/temperature conditions using cyclic and constant flow rate injection strategies. The fracturing results are compared with results using different fracturing fluids in terms of controlling fracture propagation rates, fracture hydraulic conductivity, breakdown pressures and volumes of fluids required. Methods/Procedures/Process: In all tests, water was initially injected into the rock to increase the water saturation before the fracturing processes to simulate actual geothermal reservoir conditions. For the cyclic injection, one complete cycle consisted of (1) a PAA slug (or water slug) injection followed by (2) CO2 injection to initiate the fracture. In the second step of the first cycle, the pressure of CO2 is increased until a maximum pressure is reached (fracture is initiated at this moment), and then the injection of CO2 is allowed for another 30 seconds to propagate the fracture. Then, the two-step cycle of PAA followed by CO2 injection (up to 2-4 mL/min) was continued. For the constant flow rate injection strategies, the initial water saturation was increased by injecting water at 1000 psi and 200°C for three days. After that, an initial slug of water, CO2, or PAA was injected and then fracturing was initiated and propagated by injecting CO2 at a constant flow rate. Applications/Significance/Novelty: The results of this study suggest that water saturation, especially near the wellbore region, will significantly affect the fracturing fluid transmission into the rock porous media by changing the relative permeability of CO2 or water, thus affecting the fracture initiation and propagation. In this study, fracturing with cyclic injection or constant flow rate injection methods were performed using three different kinds of fluids systems. These fluids are water, CO2, or CO2 with PAA. Splitting the rock samples in half after fracturing reveals that the fracture propagation is significantly limited under these high water saturated conditions compared to dry initial conditions: The fractures propagate less than 1/3 length of the distance from the wellbore to rock surface, and in some cases no fracture is generated. This may be caused by the fact that leak-off is dominating the fracturing process and the injected fluid flow rate is not high enough to overcome the leak-off even under high flow rate injection conditions. Additionally, CO2 could be leaking off into the wellbore annulus and this may be making it more difficult to generate pressure gradients away from the near-wellbore region.

Jian, Guoqing↗

Effect of initial water saturation on the performance of fracturing fluids with and without polyallylamine under simulated EGS conditions

Objectives/Scope: StimuFrac (US Patents 9,873,828 B2 and 9,447,315 B2), a CO 2 - reactive polymer aqueous solution [polyallylamine (PAA) 1wt% in water] combined with CO 2 , can be used as a potentially less water-intensive fracturing fluid for enhanced geothermal systems (EGS). Our previous results show that in hot dry rock (HDR), PAA/CO 2 fracturing fluids outperformed other fluids such as water, CO 2 , and CO 2 /water in generating large fractures with less fluid consumed. The objective of this work is to investigate the effect of initial water saturation on the performance of StimuFrac by conducting hydraulic fracturing tests with ½ foot cubic rock samples held under representative EGS stress/temperature conditions and by using cyclic injection strategies (under constant injection rate). The resulting fracture hydraulic conductivities, breakdown pressures, and volumes of fluids required are compared. Methods/Procedures/Process: To simulate geothermal reservoir conditions, in all tests, the rock sample was held under triaxial confinement and at 200 °C, and different volumes of water were initially injected into the rock sample before any fracturing processes were initiated. For the single-cycle PAA (or water) alternating CO 2 (PAG or WAG) injection fracturing experiments, one complete cycle consisted of two steps: (1) injecting a PAA slug (or water slug) followed by (2) injecting CO 2 to initiate and propagate the fracture. For experiments involving multiple injection cycles, the CO 2 injection pressure is increased until it peaks and begins to decline (indicating fracture initiation at this moment), and then continued being injected for another 30 seconds to propagate the fracture. Then, these two-step cycles [injection of PAA (or water) followed by CO 2 injection (up to 2-4 mL/min)] are repeated. Applications/Significance/Novelty: The results of this study suggest that water saturation significantly affects the fracturing fluid transmission into the rock pore space, thus affecting the fracture initiation and propagation. In this study, fracturing tests via a single injection cycle or multiple injection cycles were performed. Splitting the rock samples in half after testing reveals that fracture propagation is significantly limited under high water saturation conditions (three-day initial water injection) compared to stimulation experiments performed in hot dry rock. The fractures propagate less than 1/3 of the distance from the wellbore to the outer rock surface, and in some cases, no fracture is generated. This may be caused by leak-off dominating the fracturing process and the fluid injection rate is insufficient to overcome leak-off, even under high injection rate conditions. Additionally, CO 2 could be leaking off into the wellbore annulus and this may be making it more difficult to generate sufficiently high-pressure gradients away from the near-wellbore region. Under low water saturation conditions (dry rock or after 1-day initial water injection), PAA/CO 2 consistently generated significantly larger fractures compared with the other fluids. CO 2 generated large fractures only in the hot dry rock and only when using high injection rates, though data variability is high.

58 GEOSCIENCES↗

Synergistic effect of microstructure and defects on the initiation of fatigue cracks in additively manufactured Inconel 718

Fatigue cracks in additively manufactured (AMed) Inconel 718 (IN-718) in machined surface condition often initiate from persistent slip bands (PSBs) unlike other popular AM alloys such as 17-4 PH stainless steel or Ti-6Al-4V, where fatigue crack initiation is exclusively from volumetric defects; therefore, a competition between PSB- vs. defect- mediated crack initiation clearly exists. To shed light on the factors governing the competition, this study investigates the characteristics of cyclic strain localization, PSB formation, and crack initiation via crystal plasticity (CP) modeling of cyclic loading on polycrystalline aggregates which are then validated by experiments. In this work, a physics-based, free slip distance (FSD) dependent slip strength evolution law is proposed, which is shown to enable the CP model to simulate the heterogeneous strain distribution in IN-718. Implementing a crack initiation criterion based on strain contrast, the locations and lives for crack initiation can also be calculated. It is shown that both FSD and resolve shear stress influence the strain localization and crack initiation behaviors. The distribution of a localization parameter calculated based on the multiplication of FSD and Schmid factor within a grain is found to correlate well with the locations of PSBs. The maximum values of the localization parameters within a microstructure are shown to correlate well with the experimentally obtained crack initiation lives. The presence of volumetric defects in IN-718 generally do not impact strain localization behavior unless their size is large compared to the grain size.

42 ENGINEERING↗

Three-dimensional simulations of reshocked inclined Richtmyer-Meshkov instability: Effects of initial perturbations

The effect of initial perturbations on the evolution of the inclined Richtmyer-Meshkov turbulent mixing layer before and after reshock initiated by a shock wave with Mach number 1.55 is investigated through three-dimensional (3D) simulations using the flash code. The 3D simulations aim to reproduce both predominantly single-mode and multimode interfaces between light and heavy gases (N 2 -CO 2 , Atwood number, A≈0.22; amplitude to wavelength ratio of 0.088) which were created in an inclined shock tube facility to analyze the effects of initial conditions on mixing development in the entire flow field. The two-dimensional center slices of 3D simulations are compared with the experimental results to validate the computational code. Mixing width, mixed mass, mixed-mass thickness, and circulation in addition to concentration fields are shown to be in good agreement with the experimental data. The three-dimensional density and vorticity fields are first presented to qualitatively describe the flow behavior before and after reshock. Several measured density/velocity-related quantities indicate that the growth of the mixing material is strongly dependent on initial conditions. Before reshock and at early times after reshock, flow is clearly maintaining the memory of initial perturbations. However, at late time after reshock, although the large wavelength feature still dominates the flow motion, and the morphology of the two different interfaces indicates several differences, by breakdown of large-scale coherent structures to much finer scales, the memory of small scales of the multimode initial perturbation is not as clear as pre-reshock. Regarding three-dimensionality of the flow, before reshock in the multimode case, the baroclinic vorticity production, circulation, turbulent kinetic energy, and turbulent mass flux suggest that the small-scale roll-up features along the large inclined wavelength quickly evolves in all three dimensions. The coherent vortex tubes break down to smaller wormlike vortex structures, and turbulent fluctuations in the out-of-plane dimension are comparable to the spanwise direction. After reshock, this three-dimensionality of mixing growth was observed in the flow for both initial conditions. The results of this work represent a significant extension of previous computational studies performed on this specific topic. A different code with a different numerical method is validated through comparison with the experimental data. The initial perturbations are directly measured from the experimental results. Moreover, the entire three-dimensional experimental shock tube domain is simulated, and more quantities are investigated to understand the mixing mechanism and instability evolution in all three dimensions.

42 ENGINEERING↗

A Machine Learning Initializer for Newton-Raphson AC Power Flow Convergence

Power flow computations are fundamental to many power system studies. Obtaining a converged power flow case is not a trivial task especially in large power grids due to the non-linear nature of the power flow equations. One key challenge is that the widely used Newton based power flow methods are sensitive to the initial voltage magnitude and angle estimates, and a bad initial estimate would lead to non-convergence. This paper addresses this challenge by developing a random-forest (RF) machine learning model to provide better initial voltage magnitude and angle estimates towards achieving power flow convergence. This method was implemented on a real ERCOT 6102 bus system under various operating conditions. By providing better Newton-Raphson initialization, the RF model precipitated the solution of 2,106 cases out of 3,899 non-converging dispatches. These cases could not be solved from flat start or by initialization with the voltage solution of a reference case. Finally, results obtained from the RF initializer performed better when compared with DC power flow initialization, Linear regression, and Decision Trees.

random forest↗

High-efficiency, high-fidelity charge initialization of shallow nitrogen-vacancy centers in diamond

Nitrogen-vacancy (N-𝑉) centers in diamond exhibit long spin-coherence times, optical initialization, and optical-spin readout under ambient conditions, making them excellent quantum sensors. However, the conventional scheme for charge-state initialization based on off-resonant green excitation results in significant state-preparation errors, typically around 30%. One method for improving charge-state initialization fidelity is to use multicolor excitation, which has been demonstrated to achieve a near-unity preparation fidelity for bulk N-𝑉 centers by using a few milliseconds of near-infrared (NIR) (5-mW) and green (10-μ⁢W) excitation. The translation of such schemes to N-𝑉 centers near the diamond surface with higher-efficiency optical pumping would enable new applications in nanoscale sensing. Here, we demonstrate a protocol for efficient charge initialization of shallow N-𝑉 centers between 5 nm and 15 nm from the diamond surface. By carefully studying the charge dynamics of shallow N-𝑉 centers, we identify a region of parameter space that allows for near-unity (95%) charge initialization within 300 μ⁢s of NIR (905-nm, 1-mW) and green (520-nm, 10-μ⁢W) excitation. The time to 90% charge initialization can be as fast as 10 μ⁢s for 4 mW of NIR and 39 μ⁢W of green illumination. This fast, efficient charge initialization protocol will especially benefit nanoscale sensing applications in which state-preparation errors currently prohibit scaling, such as measuring higher-order multipoint correlators.

infrared techniques↗

The Influence of Shear on Deep Convection Initiation. Part I: Theory

Abstract This article introduces a novel hypothesis for the role of vertical wind shear (“shear”) in deep convection initiation (DCI). In this hypothesis, initial moist updrafts that exceed a width and shear threshold will “root” within a progressively deeper steering current with time, increase their low-level cloud-relative flow and inflow, widen, and subsequently reduce their susceptibility to entrainment-driven dilution, evolving toward a quasi-steady self-sustaining state. In contrast, initial updrafts that do not exceed the aforementioned thresholds experience suppressed growth by shear-induced downward pressure gradient accelerations, will not root in a deep-enough steering current to increase their inflow, will narrow with time, and will succumb to entrainment-driven dilution. In the latter case, an externally driven lifting mechanism is required to sustain deep convection, and deep convection will not persist in the absence of such lifting mechanism. A theoretical model is developed from the equations of motion to further explore this hypothesis. The model indicates that shear generally suppresses DCI, raising the initial subcloud updraft width that is necessary for it to occur. However, there is a pronounced bifurcation in updraft growth in the model after the onset of convection. Sufficiently wide initial updrafts grow and eventually achieve a steady state. In contrast, insufficiently wide initial updrafts shrink with time and eventually decay completely without external support. A sharp initial updraft radius threshold discriminates between these two outcomes. Thus, consistent with our hypothesis and observations, shear inhibits DCI in some situations, but facilitates it in others.

42 ENGINEERING↗

COMPUTATIONAL MODELING OF IGNITION AND PREMIXED FLAME PROPAGATION INITIATED BY A PRE-CHAMBER TURBULENT JET

Addressing the pressing need for reduced carbon emissions, Turbulent Jet Ignition (TJI) emerges as a promising technology for ultra-lean combustion, offering enhanced thermal efficiencies and minimized cyclic variability in spark-ignited engines. To facilitate rapid testing and integration of this technology, a robust computational modeling framework is crucial. This study delves into the predictive capabilities of computational models for main-chamber ignition and premixed flame propagation using a single-cycle TJI rig measured by Biswas et al. (Applied Thermal Engineering, vol 106, 2016). Employing an open-source compressible flow simulation solver with Large Eddy Simulation (LES) for turbulence modeling, the investigation integrates the conventional Laminar Finite Rate Chemistry (LFRC) model alongside the transported Probability Density Method (PDF) for turbulence-chemistry interaction. A fully-consistent Eulerian Monte-Carlo Fields (EMCF) method is utilized to approximate the transported PDF, while Interaction by Exchange with Mean is employed to close micro-mixing terms in stochastic differential equations. A reduced chemical reaction mechanism with 21 species and 84 reactions (DRM-19) is used for solving chemical kinetics, and a double Gaussian energy deposition model is used to approximate the spark ignition in the pre-chamber. An unstructured O-grid mesh with 0.3 million cells in the prechamber and 1 million cells in the main chamber is employed. Results are divided into two phases: pre-chamber initialization and full TJI simulations. Validation of the predicted pre-chamber flame propagation and the lean ignition in the main-chamber is carried out by using available experimental data. Under quiescent conditions, both the LFRC and transported PDF methods largely underestimate the flame speed and subsequent pressure growth in the pre-chamber. A linear momentum forcing technique is applied to investigate the impact of initial turbulence in the pre-chamber, demonstrating a notable influence on flame propagation. Fine-tuning of the forcing coefficient reproduces the sudden pressure growth observed in the experiment. The experimentally validated pre-chamber simulation serves as the initial condition for the full TJI simulations. It is found that the LFRC model fails to predict lean-ignition in the main-chamber, resulting in a misfiring event. Incorporation of turbulence-chemistry interaction using the transported PDF method substantially improves the prediction of the ignition event in the main-chamber, achieving fair qualitative agreement and quantitative validation of combustion parameters within ±10% of the reported experimental data. The rich simulation results consisting of a full set of statistical description of the thermo-chemical states enable us to gain deep insights into the ignition mechanisms in the main chamber, which is limited when done experimentally. A novel dual ignition phenomenon is revealed in the TJI rig for the first time. Initially, a primary ignition kernel is formed at a downstream location which eventually detaches from the main jet. As the jet momentum decreases, a secondary ignition event follows, this time at a more upstream location which eventually combines with the primary ignition kernel to form a single connected flame front. Investigation of these ignition sequences in chemical composition space reveal distinct differences between the two. The primary ignition event in the main-chamber is followed by a large concentration of active radicals from the pre-chamber jet, accelerating the chain-branching steps, characterizing what has been referred to as flame ignition. In contrast, the secondary ignition occurs in the absence of active radicals in the pre-chamber jet, hence characterized as jet ignition. Further analysis of the effect of pre-chamber jet characteristics on lean ignition in the main-chamber is conducted by setting up cases with different initial pressure ratios (por) between the two chambers, a non-dimensional parameter, ranging from 1.2 to 3.2. As the initial pressure ratio increases, jet momentum increases, with dual ignition observed in cases above por= 2.2. Case with por= 3.2 lead to misfiring. The effect of ignition sequence on global combustion characteristics of TJI is analyzed. Dual ignition events lead to non-monotonicity in combustion characteristics such as global reaction progress variable, flame penetration, and global heat release rate. In dual ignition events, although the rate of fuel consumption and global heat release rate is initially lower, the secondary ignition leads to a sudden increase in flame surface area, resulting in a sudden jump and promoting the overall performance of the TJI system.

42 ENGINEERING↗

Improved subseasonal-to-seasonal precipitation prediction of climate models with nudging approach for better initialization of Tibetan Plateau-Rocky Mountain Circumglobal wave train and land surface conditions

Abstract Reliable subseasonal-to-seasonal (S2S) precipitation prediction is highly desired due to the great socioeconomical implications, yet it remains one of the most challenging topics in the weather/climate prediction research area. As part of the Impact of Initialized Land Temperature and Snowpack on Sub-seasonal to Seasonal Prediction (LS4P) project of the Global Energy and Water Exchanges (GEWEX) program, twenty-one climate models follow the LS4P protocol to quantify the impact of the Tibetan Plateau (TP) land surface temperature/subsurface temperature (LST/SUBT) springtime anomalies on the global summertime precipitation. We find that nudging towards reanalysis winds is crucial for climate models to generate atmosphere and land surface initial conditions close to observations, which is necessary for meaningful S2S applications. Simulations with nudged initial conditions can better capture the summer precipitation responses to the imposed TP LST/SUBT spring anomalies at hotspot regions all over the world. Further analyses show that the enhanced S2S prediction skill is largely attributable to the substantially improved initialization of the Tibetan Plateau-Rocky Mountain Circumglobal (TRC) wave train pattern in the atmosphere. This study highlights the important role that initial condition plays in the S2S prediction and suggests that data assimilation technique (e.g., nudging) should be adopted to initialize climate models to improve their S2S prediction.

54 ENVIRONMENTAL SCIENCES↗

Effects of hydrogen partial pressure on crack initiation and growth rate in vintage X52 steel

There is an increasing interest in ensuring compatibility of existing natural gas infrastructure with conveyance of hydrogen, especially for vintage (pre-1970s) pipeline steels. While hydrogen is known to affect the fatigue and fracture resistance of these materials, there is a lack of data on its effects on crack initiation at low hydrogen partial pressure. To address this gap, the current work presents a series of fatigue tests on vintage API Grade X52 steel in pure nitrogen, air and gaseous hydrogen at partial pressures of 1 and 207 bar. Circumferential notch tension (CNT) specimens with direct current potential difference (DCPD) measurements are used to get S–N curves for crack initiation and failure, and compact tension (CT) tests to assess crack growth rates. Results indicate that air accelerates crack initiation, low hydrogen partial pressure affects the crack growth rate, and higher pressures have the largest impact on both. Surprisingly, crack initiation is faster in air than at 1 bar hydrogen partial pressure. The CNT tests also reveal that the orientation of the banded microstructure has no effect on the crack initiation site, but it influences its growth behavior. Moreover, fractography shows that hydrogen also promotes instances of quasi-cleavage and intergranular fracture, linked to embrittlement of the material. Here, these results demonstrate that, while hydrogen may impact the entirety of the fatigue process, its effects on the early stages of damage accumulation become relevant only at larger pressures. More comprehensive studies of crack initiation in hydrogen atmospheres will be critical to future codes and standards for hydrogen infrastructure.

Circumferential notch tension↗