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At least 1,063 records · Page 59

Advanced Solution Methods for Microkinetic Models of Catalytic Reactions: A Methanol Synthesis Case Study

Microkinetic models, combined with experimentally measured reaction rates and orders, play a key role in elucidating detailed reaction mechanisms in heterogeneous catalysis and have typically been solved as systems of ordinary differential equations. In this work, we demonstrate a new approach to fitting those models to experimental data. For the specific example treated here, by reformulating a typical microkinetic model for a continuous stirred tank reactor to a system of nonlinear equations, we achieved a 1000-fold increase in solution speed. The reduced computational cost allows a more systematic search of the parameter space, leading to better fits to the available experimental data. We applied this approach to the problem of methanol synthesis by CO/CO2 hydrogenation over a supported-Cu catalyst, an important catalytic reaction with a large industrial interest and potential for large-scale CO2 chemical fixation.

Environmental Molecular Sciences Laboratory↗

Quantifying the impact of temporal analysis of products reactor initial state uncertainties on kinetic parameters

The temporal analysis of products (TAP) reactor, a transient kinetic tool, provides users with information as the catalyst state evolves. However, the state of the art for TAP uncertainty quantification only considers the experimental noise present in the outlet flow signal. Additional sources of uncertainty, including, but not limited to, initial surface coverages, the catalyst zone location, the inert void fraction, and the gas pulse intensity and pulse delay, are not included. For this reason, a framework for quantifying all uncertainty sources present in TAP experiments is presented and applied to a carbon monoxide oxidation case study. Herein, two methods for quantifying these sources of uncertainty are introduced. The first utilizes initial state sensitivities to approximate the parameter variances, as well as to provide insights into the structural certainty of the model. The second generates parameter confidence distributions through an ensemble-based sampling algorithm. This initial state covariance matrix can ultimately be merged with the experimental noise covariance matrix, providing a unified description of the parameter uncertainties for a single TAP experiment.

36 MATERIALS SCIENCE↗

Sequential formulation of all‐way coupled finite strain thermoporomechanics for largely deformable gas hydrate deposits

We develop a numerically stable sequential formulation of thermoporomechanics for largely deformable gas hydrate deposits, extended from the fixed stress split of infinitesimal transformation. Constitutive equations are based on the total Lagrangian approach for both flow and geomechanics, including dynamic full tensor permeability and thermal conductivity updated from the deformation gradient. For space discretization, we take the cell-centered finite volume and node-based finite element method for flow and geomechanics, respectively. Then, we propose a sequential implicit method for all-way coupled thermoporomechanics, where the nonisothermal multiphase flow problem of gas hydrates is solved implicitly first and then the geomechanics problem is solved implicitly at the next step. During solution of the flow problem, we fix the rate of first Pioal total stress for numerical stability as well as apply porosity correction and entropy correction to account for geomechanical effects. We test numerical examples where flow and geomechanics parameters are based on deep oceanic gas hydrate deposits. When applying depressurization, even though the results between the infinitesimal transformation and finite strain geomechanics are similar in the early stages due to small deformation, we find differences between them in the late times as deformation becomes large. Accordingly, permeability and thermal conductivity tensors become nonisotropic full tensors although they are initially isotropic. Furthermore, we identify numerical stability of the developed sequential method from the test cases that exhibit the highly complex coupled gas hydrate systems with large deformation. Thus, the proposed sequential formulation can be applied in largely deformable gas hydrate systems.

42 ENGINEERING↗

Veneziano variations: how unique are string amplitudes?

String theory offers an elegant and concrete realization of how to consistently couple states of arbitrarily high spin. But how unique is this construction? In this paper we derive a novel, multi-parameter family of four-point scattering amplitudes exhibiting i) polynomially bounded high-energy behavior and ii) exchange of an infinite tower of high-spin modes, albeit with a finite number of states at each resonance. These amplitudes take an infinite-product form and, depending on parameters, exhibit mass spectra that are either unbounded or bounded, thus corresponding to generalizations of the Veneziano and Coon amplitudes, respectively. For the bounded case, masses converge to an accumulation point, a peculiar feature seen in the Coon amplitude but more recently understood to arise naturally in string theory [1]. Importantly, our amplitudes contain free parameters allowing for the customization of the slope and offset of the spin-dependence in the Regge trajectory. We compute all partial waves for this multi-parameter class of amplitudes and identify unitary regions of parameter space. For the unbounded case, we apply similar methods to derive new deformations of the Veneziano and Virasoro-Shapiro amplitudes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Computing black hole partition functions from quasinormal modes

We propose a method of computing one-loop determinants in black hole space-times (with emphasis on asymptotically anti-de Sitter black holes) that may be used for numerics when completely-analytic results are unattainable. The method utilizes the expression for one-loop determinants in terms of quasinormal frequencies determined by Denef, Hartnoll and Sachdev in [1]. A numerical evaluation must face the fact that the sum over the quasinormal modes, indexed by momentum and overtone numbers, is divergent. A necessary ingredient is then a regularization scheme to handle the divergent contributions of individual fixed-momentum sectors to the partition function. To this end, we formulate an effective two-dimensional problem in which a natural refinement of standard heat kernel techniques can be used to account for contributions to the partition function at fixed momentum. We test our method in a concrete case by reproducing the scalar one-loop determinant in the BTZ black hole background. Furthermore, we then discuss the application of such techniques to more complicated spacetimes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Loops in AdS from conformal field theory

We propose and demonstrate a new use for conformal field theory (CFT) crossing equations in the context of AdS/CFT: the computation of loop amplitudes in AdS, dual to non-planar correlators in holographic CFTs. Loops in AdS are largely unexplored, mostly due to technical difficulties in direct calculations. We revisit this problem, and the dual 1=N expansion of CFTs, in two independent ways. The first is to show how to explicitly solve the crossing equations to the first subleading order in 1=N 2 , given a leading order solution. This is done as a systematic expansion in inverse powers of the spin, to all orders. These expansions can be resummed, leading to the CFT data for nite values of the spin. Our second approach involves Mellin space. We show how the polar part of the four-point, loop-level Mellin amplitudes can be fully reconstructed from the leading-order data. The anomalous dimensions computed with both methods agree. In the case of $\phi$ 4 theory in AdS, our crossing solution reproduces a previous computation of the one-loop bubble diagram. We can go further, deriving the four-point scalar triangle diagram in AdS, which had never been computed. In the process, we show how to analytically derive anomalous dimensions from Mellin amplitudes with an in nite series of poles, and discuss applications to more complicated cases such as the N = 4 super-Yang-Mills theory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Long-Term Evaluation of Percutaneous Groin Access for EVAR

Background: Percutaneous endovascular aneurysm repair (PEVAR) has been shown to have high success rates, shorter operating times and length of stay compared to open access. However, there exists a lack of long-term follow-up data on these patients, and questions remain regarding longer-term outcomes. This study aims to assess the long-term complications and evolution of accessed vessels post-PEVAR. Methods: Sixty-one cases of bilateral PEVAR (122 groins) with > 36 months follow-up were analysed. Vessel diameter, calcification, dissection, lymphocele, pseudoaneurysm and thrombus formation were reviewed at 30th day and at the most recent follow-up CT. Notes were reviewed for groin infections, haematomas and nerve injury. Complications were considered ‘major’ if they required intervention or treatment. Results: Mean follow-up time from procedure to most recent scan was 49.9 months. There were no major short- or long-term complications. The early complication rate was 9.8%, with six pseudoaneurysms, four dissections, one thrombus, one nerve injury and no lymphoceles, haematomas or groin infections. The long-term complication rate was 0.8%, with only one pseudoaneurysm. The remainder of early complications resolved naturally without intervention. Accessed vessel showed significantly (P ≤ 0.05) increased diameter and calcification between 30th day and last follow-up scan. Conclusion: This study provides the largest clinical cohort and the longest mean follow-up time reported in the literature and demonstrates the long-term safety of PEVAR. PEVAR has a very low long-term complication rate, without any major complications in our cohort. The accessed common femoral arteries do not show stenosis or thrombosis. Minor short-term complications appear to gradually resolve without intervention. Larger multi-centre studies are recommended.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Catheter-Directed Fenestration for Branch Vessel Reconnection in Aortic Dissection Using a Novel Diamond-Tipped Chronic Total Occlusion Drilling Device: A Technical Report

Purpose: Aortic dissection is a complex condition with high morbidity and mortality. Endovascular treatments including percutaneous fenestration can be used to manage branch vessel ischaemia or risk of aortic rupture. A variety of techniques for aortic fenestration have been described. We describe the novel use of the TruePath Chronic Total Occlusion (CTO) device for aortic intimal fenestration to achieve side branch reconnection. Materials and Methods: We present three cases of aortic dissection presenting with symptoms of aortic side branch occlusion and end organ malperfusion, treated with aortic fenestration using the TruePath CTO device via trans-brachial and trans-femoral approaches. Results: Technical success was achieved in all three cases. No complications were encountered. Flow was restored in compromised visceral branches. Branches remained patent on follow-up CT angiography over a minimum 2.5-year follow-up period. Conclusion: Percutaneous aortic fenestration techniques enable a minimally invasive approach to treat visceral branch malperfusion associated with aortic dissection. The TruePath CTO device improves the control of the fenestration procedure with the potential to improve efficacy and safety.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Prediction of gas hydrate saturation using machine learning and optimal set of well-logs

We report resistivity and acoustic logs are widely used to estimate gas hydrate saturation in various sedimentary systems using one of the two popular methods ((1) acoustic velocity and (2) electrical resistivity), but the limitations of these two methods are often overlooked, which include (i) well-specific calibration of empirical exponents in the electrical resistivity method, (ii) assumption of known pore morphology for gas hydrates in the acoustic velocity method, and (iii) presence of unknown mineralogy and bulk modulus terms in the acoustic velocity method. NMR-density porosity-derived gas hydrate saturation based on the analysis of the transverse magnetization relaxation time (T2) is considered the most precise method, but acquisition of NMR-based logs is limited at relatively recent drilled sites; additionally, its use in conventional oil and gas reservoirs is not that common due to higher cost and operational deployment limitations associated with acquiring NMR well-logs. This study proposes a new method that predicts gas hydrate saturation (S h ) for any well using porosity, bulk density, and compressional wave (P wave) velocity well-logs with neural network (or stochastic gradient descent regression) without any well-specific calibration and/or other aforementioned shortcomings of the existing methods. The method is developed by examining the underlying dependency between S h and different combinations of well-logs, chosen from 6 routine logs, with 12 different machine learning (ML) algorithms. The accuracy of the proposed method in predicting S h is ~ 84%, which is better than the accuracy of seismic and electrical resistivity methods (≤ 75%) per the results reported by three different studies. The robustness of the method in the specific case of permafrost-associated gas hydrates is demonstrated with well-log data from two wells drilled on the Alaska North Slope.

58 GEOSCIENCES↗

Hybrid data-driven cement-stabilized soil design: An integration of machine learning, multi-objective optimization, and life cycle assessment

Soil stabilization is crucial in geotechnical engineering, yet conventional methods are often time-consuming, resource-intensive, and environmentally unsustainable. Despite growing interest in Machine Learning (ML) and optimization tools for mix design, few studies integrate these methods with decision-making techniques and environmental assessment to support practical implementation. This study proposes a hybrid data-driven framework for predicting strength, optimizing mix compositions, and evaluating environmental impacts via life cycle assessment of cement-stabilized soft soils. Six ML models were evaluated, and the top-performing eXtreme Gradient Boosting (XGB) model was further improved using the Grey Wolf Optimizer (GWO). The optimized XGB-GWO model, integrated with a polynomial cost function, served as the objective function in a multi-objective optimization problem solved via the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), with final mix selection guided by the entropy-weighted TOPSIS method. Validation through a case study produced mix designs offering superior strength-cost trade-offs, with the optimal mix achieving 2243.2 kPa unconfined compressive strength and a 16.07 % reduction in carbon emissions compared to the highest-cost design. In conclusion, this study offers a sustainable, scalable approach to soil stabilization and supports informed decision-making in construction.

Life cycle assessment↗

Machine learning-assisted identification of potential sources of bias in measurements of prompt-fission neutron spectra

Unrecognized sources of uncertainty (USU) can bias the reported mean and/or covariance of experimental nuclear data. These biases, in turn, can propagate through evaluated nuclear data to application simulations or may poorly inform nuclear theory that is fitted to the experimental data. Such unknown sources of bias must be tied to the inherent physical constituents of the measurements such as the characteristics of a detector response or a background reduction technique. Here, in this article, a sparse Bayesian learning model is used to support experts in their efforts to identify and characterize USU in experimental prompt fission neutron spectra (PFNS) for spontaneous fissioning of 252 Cf by linking observed biases to features of the measurement system. Three different bias components were found. The first acts as a verification case for the algorithm as it identifies a bias coming from a well-known source related to the use of 6 Li in the neutron detection system. The second two cases demonstrate how this method can benefit the evaluation of experimental nuclear data by identifying, quantifying, and relating unknown biases to potential causes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A biophysical approach to the performance diagnosis of human–building energy interaction: Information (bits) modeling, algorithm, and indicators of energy flow complexity

Highlights: • Energy-related human-building interaction is analyzed at the biophysical system scale. • Energy flow-networking model of environmental building performance is suggested. • Information is suggested as a holistic building performance metric. - Abstract: This article addresses the utmost upstream impacts of human–building energy interaction by proposing a network-based model, algorithms, and indicators. Hypothesizing that human behavior is a key factor for the symbiotic development of building and the geobiosphere system, the author seeks emergy (spelled with an “m”)-information integrated measures to indicate dynamic system-level performance of the interaction with building energy flow topology. To validate the hypothesis and methods, four representative building cases were tested on the building form (envelope) of (i) a building with no occupant intervention (baseline), (ii) a building controlled by responsive human behavior (bioclimatic adaptation), (iii) a building with reinforced insulation and behavior-dominated control (passive design), and (iv) a net-zero energy building (NZEB). The results demonstrate that adaptive human behavior in building operation increases the information content and complexity of energy-flow networking, improving performance and sustainability. Findings also reveal that increasing information, complexity, and power (energy availability over time) parallel the general energetic features of developing biophysical systems (greater feedback, internalization, and recycling of materials and energies). It becames clear that active behavioral response is a dominant agent of sustainable environments even on a far broader system scale.

54 ENVIRONMENTAL SCIENCES↗

Energy efficiency as a means to expand energy access: A Uganda roadmap

While energy efficiency can contribute significantly towards improving access to modern energy services, energy sector investments in many developing countries have largely focused on increasing energy access by increasing supply. This is because the links between energy efficiency and energy access, is often overlooked. This oversight of energy efficiency is frequently a missed opportunity, as efficiency is often a very cost-effective energy resource. In combination with grid expansion and new clean energy generation, efficiency efforts can help to ensure that reliable power is provided to the maximum number of customers at a lower cost than would be required to increase generation alone. Here in this paper we describe an analysis method for determining a country's energy efficiency priorities and devising an action plan to integrate energy efficiency as a resource for meeting a nation's energy access goals. We illustrate this method with a detailed case study of Uganda. If the most efficient technologies on the market were adopted in Uganda, 442 MW of generation-level demand could be offset and energy access for an additional 6 M rural customers could be achieved by 2030. Of this technical potential for efficiency, 91% is cost-effective, and 47% is economically achievable under conservative assumptions.

Sub-Saharan Africa↗

A data-driven sensor placement approach for detecting voltage violations in distribution systems

Stochastic fluctuations in power injections from distributed energy resources (DERs) combined with load variability can cause constraint violations (e.g., exceeded voltage limits) in electric distribution systems. To monitor grid operations, sensors are placed to measure important quantities such as the voltage magnitudes. Here, in this paper, we consider a sensor placement problem which seeks to identify locations for installing sensors that can capture all possible violations of voltage magnitude limits. We formulate a bilevel optimization problem that minimizes the number of sensors and avoids false sensor alarms in the upper level while ensuring detection of any voltage violations in the lower level. This problem is challenging due to the nonlinearity of the power flow equations and the presence of binary variables. Accordingly, we employ recently developed conservative linear approximations of the power flow equations that overestimate or underestimate the voltage magnitudes. By replacing the nonlinear power flow equations with conservative linear approximations, we can ensure that the resulting sensor locations and thresholds are sufficient to identify any constraint violations. Additionally, we apply various problem reformulations to significantly improve computational tractability while simultaneously ensuring an appropriate placement of sensors. Lastly, we improve the quality of the results via an approximate gradient descent method that adjusts the sensor thresholds. We demonstrate the effectiveness of our proposed method for several test cases, including a system with multiple switching configurations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

CO 2 storage site characterization using ensemble-based approaches with deep generative models

Estimating spatially distributed properties such as permeability from available sparse measurements is a great challenge in efficient subsurface CO 2 storage operations. In this paper, a deep generative model that can accurately capture complex subsurface structure is tested with an ensemble-based inversion method for accurate and accelerated characterization of CO 2 storage sites. We chose Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) for its realistic reservoir property representation and Ensemble Smoother with Multiple Data Assimilation (ES-MDA) for its robust data fitting and uncertainty quantification capability. WGAN-GP are trained to generate high-dimensional permeability fields from a low-dimensional latent space and ES-MDA then updates the latent variables by assimilating available measurements. Several subsurface site characterization examples including Gaussian, channelized, and fractured reservoirs are used to evaluate the accuracy and computational efficiency of the proposed method and the main features of the unknown permeability fields are characterized accurately with reliable uncertainty quantification. Furthermore, the estimation performance is compared with a widely-used variational, i.e., optimization-based, inversion approach, and the proposed approach outperforms the variational inversion method in several benchmark cases. We explain such superior performance by visualizing the objective function in the latent space: because of nonlinear and aggressive dimension reduction via generative modeling, the objective function surface becomes extremely complex while the ensemble approximation can smooth out the multi-modal surface during the minimization. This suggests that the ensemble-based approach works well over the variational approach when combined with deep generative models at the cost of forward model runs unless convergence-ensuring modifications are implemented in the variational inversion.

42 ENGINEERING↗

A method to identify weak points of interconnection of renewable energy resources

The increasing penetration of renewable energy resources (RERs) is challenging power grid planning and operation in maintaining grid reliability. Potential power grid reliability and stability issues may arise when large-scale RERs are connected to a weak power grid. These issues may become more significant due to the mutual interactions among RERs that are interconnected electrically close through a power network. Weakness analysis based on grid strength assessment is useful for identifying the potential weak grid issues. However, when taking into account the impact of the interactions among RERs, the weakness analysis becomes computationally challenging. Different combinations of points of interconnections (POIs) of RERs may have different impacts on grid strength at each POI. Due to the combination nature, such weakness analysis may be time-consuming when identifying the weakest combination of POIs from a large number of potential candidates in realistic power grids. To address this concern, the impact of the power network structure on grid strength is analyzed in this paper. It is found that the impact mainly depends on the impedance ratios at POIs. The findings can be summarized as two criteria to develop a recursive method for fast identification of the weakest combination in this paper. The efficacy of the proposed method is demonstrated through case studies on the IEEE 39-bus system and a realistic power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Proton Radiotherapy for Prostate Cancer Is Not Associated With Post-Treatment Testosterone Suppression

Purpose: Three independent studies of photon (x-ray) radiotherapy (RT) for prostate cancer have demonstrated evidence of testosterone suppression after treatment. The present study was undertaken to determine whether this would also be the case with conformal protons. Methods and Materials: Between August 2006 and October 2007, 171 patients with low- and intermediate-risk prostate cancer were enrolled and underwent treatment according to University of Florida Proton Therapy Institute institutional review board-approved PR01 and PR02 protocols. Of the 171 patients, 18 were excluded because they had received androgen deprivation therapy either before (n = 17) or after (n = 1) RT. The pretreatment serum testosterone level was available for 150 of the remaining 153 patients. These 150 patients were included in the present study. The post-treatment levels were compared with the pretreatment levels. Results: The median baseline pretreatment serum testosterone level was 357.9 ng/dL. The median post-treatment testosterone value was 375.5 ng/dL at treatment completion (p = .1935) and 369.9 ng/dL (p = .1336), 348.7 ng/dL (p = .7317), 353.4 ng/dL (p = .6996), and 340.9 ng/dL (p = .1669) at 6, 12, 18, and 24 months after proton therapy, respectively. Conclusions: Conformal proton therapy to the prostate, as delivered using University of Florida Proton Therapy Institute PR01 and PR02 protocols, did not appear to significantly affect the serum testosterone levels within 24 months after RT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Peripheral Dose Heterogeneity Due to the Thread Effect in Total Marrow Irradiation With Helical Tomotherapy

Purpose: To report potential dose heterogeneity leading to underdosing at different skeletal sites in total marrow irradiation (TMI) with helical tomotherapy due to the thread effect and provide possible solutions to reduce this effect. Methods and Materials: Nine cases were divided into 2 groups based on patient size, defined as maximum left-to-right arm distance (mLRD): small mLRD (≤47 cm) and large mLRD (>47 cm). TMI treatment planning was conducted by varying the pitch and modulation factor while a jaw size (5 cm) was kept fixed. Ripple amplitude, defined as the peak-to-trough dose relative to the average dose due to the thread effect, and the dose–volume histogram (DVH) parameters for 9 cases with various mLRD was analyzed in different skeletal regions at off-axis (eg, bones of the arm or femur), at the central axis (eg, vertebrae), and planning target volume (PTV), defined as the entire skeleton plus 1-cm margin. Results: Average ripple amplitude for a pitch of 0.430, known as one of the magic pitches that reduce thread effect, was 9.2% at 20 cm off-axis. No significant differences in DVH parameters of PTV, vertebrae, or femur were observed between small and large mLRD groups for a pitch of ≤0.287. Conversely, in the bones of the arm, average differences in the volume receiving 95% and 107% dose (V95 and V107, respectively) between large and small mLRD groups were 4.2% (P=.016) and 16% (P=.016), respectively. Strong correlations were found between mLRD and ripple amplitude (rs=.965), mLRD and V95 (rs=−.742), and mLRD and V107 (rs=.870) of bones of the arm. Conclusions: Thread effect significantly influences DVH parameters in the bones of the arm for large mLRD patients. By implementing a favorable pitch value and adjusting arm position, peripheral dose heterogeneity could be reduced.

62 RADIOLOGY AND NUCLEAR MEDICINE↗