Computational Results Research Articles

Multistage stochastic programming for integrated network optimization in hurricane relief logistics and evacuation planning

AbstractIn this article, we study the integrated hurricane relief logistics and evacuation planning (IHRLEP) problem, integrating hurricane evacuation and relief item pre‐positioning operations that are typically treated separately. We propose a fully adaptive multistage stochastic programming (MSSP) model and solution approaches based on two‐stage stochastic programming (2SSP). Utilizing historical forecast errors modeled using the auto‐regressive model of order one, we generate hurricane scenarios and approximate the hurricane process as a Markov chain, and each Markovian state is characterized by the hurricane's location and intensity attributes. We conduct a comprehensive numerical experiment based on case studies motivated by Hurricane Florence and Hurricane Ian. Through the computational results, we demonstrate the value of fully adaptive policies given by the MSSP model over static ones given by the 2SSP model in terms of the out‐of‐sample performance. By conducting an extensive sensitivity analysis, we offer insights into how the value of fully adaptive policies varies in comparison to static ones with key problem parameters.

Stochastic Resource Allocation Problems: Minmax and Maxmin Solutions

Problem definition: Min-max or max-min objective criteria naturally arise in many resource allocation applications, especially when the attendant goal involves distribution of a limited resource across multiple subsystems, locations, or activities. Each has a different consumption rate of the resource. In this setting, the decision maker is interested in optimizing the system performance, which can be measured in terms of the smallest or largest order statistic across subsystems. Examples include the allocation of health resources to maximize the first runout time or to minimize the maximum delay. Methodology/results: In the literature, there are no unified theoretical and computational results on the optimal allocations for these problems. Thus, in this paper, we develop key theoretical properties of the attendant stochastic resource allocation problems, providing a technical condition for the objective functions to have favorable properties, upon which we derive novel optimal allocation rules with clear interpretation. Managerial implications: The proportional allocation rule can be interpreted as a robust solution when the full distribution of the interarrival time is unknown. It generally has poor performance, especially when the resource consumption rates vary across locations, which happens regularly in practice. Our allocation rule is exact and should be used for the allocation of scarce resources—that is, when the number of resources per location is limited, which is often encountered in healthcare settings.

A fractional time-stepping method for unsteady thermal convection in non-Newtonian fluids

We propose a fractional-step method for the numerical solution of unsteady thermal convection in non-Newtonian fluids with temperature-dependent physical parameters. The proposed method is based on a viscosity-splitting approach, and it consists of four uncoupled steps where the convection and diffusion terms of both velocity and temperature solutions are uncoupled while a viscosity term is kept in the correction step at all times. This fractional-step method maintains the same boundary conditions imposed in the original problem for the corrected velocity solution, and it eliminates all inconsistencies related to boundary conditions for the treatment of the pressure solution. In addition, the method is unconditionally stable, and it allows the temperature to be transported by a non-divergence-free velocity field. In this case, we introduce a methodology to handle the subtle temperature convection term in the error analysis and establish full first-order error estimates for the velocity and the temperature solutions and 1/2-order estimates for the pressure solution in their appropriate norms. Three numerical examples are presented to demonstrate the theoretical results and examine the performance of the proposed method for solving unsteady thermal convection in non-Newtonian fluids. The computational results obtained for the considered examples confirm the convergence, accuracy, and applicability of the proposed time fractional-step method for unsteady thermal convection in non-Newtonian fluids.

Photochromic reaction pathways of 1,1′-azobis-1,2,3-triazole: A CASSCF and spin-flip DFT study

This study employed multiconfigurational CASSCF and MS-CASPT2 methods to investigate the photoinduced isomerization mechanism of 1,1′-azobis-1,2,3-triazole. The MS-CASPT2//CASSCF computational results indicate that the photoisomerization reaction of 1,1′-azobis-1,2,3-triazole involves a non-adiabatic transition pathway through the S2 state. After photoexcitation to the S2 state, the molecule undergoes internal conversion to reach S1-min, followed by a non-radiative transition back to the ground state. The S1/S0-CI and S1-min have similar structures and close energies, which facilitates unidirectional rotation. The weak coupling between the ground state and excited states may be due to the strong electron-withdrawing nature of the N8 chain. Additionally, using the MS-CASPT2//CASSCF computational results as a reference, we compared the differences in describing the photoisomerization process of this compound using the SF-DFT method, both qualitatively and quantitatively. The results demonstrate that the SF-DFT method significantly underestimates the energy of the S1 state. These findings are expected to deepen the understanding of non-adiabatic transitions in the photoinduced rotation of high-nitrogen compounds and provide theoretical insights for other high-nitrogen compounds that may exhibit photochromism.

Evaluating the effects of nonlocality and numerical discretization in peridynamic solutions for quasi-static elasticity and fracture

The difference between the computational peridynamic results and the corresponding exact classical solutions is contributed by the error induced by numerical discretization and the nonlocality-induced difference. To evaluate and compare these contributions and investigate their dependence on the peridynamic influence functions, in this paper, we apply different peridynamic influence functions and different horizon factors (m, the ratio between the horizon size and the grid spacing) to conduct static (or quasi-static) tensile numerical tests. We calculate the difference between the peridynamic solutions and the corresponding classical solutions for static uniaxial tension of thin plates with or without hole, the J-integral of a single crack under Mode I loading condition, and the quasi-static fracture in a perforated thin plate. For the case of uniaxial tension in a thin, homogeneous plate, we separate the effects of nonlocality and numerical discretization by implementing the boundary conditions in different ways. The numerical results show that both the effects of nonlocality and numerical discretization correspond to the nonlocal constants of the influence functions (with few exceptions). For problems with the presence of the peridynamic surface effect, such as holes, influence function with weaker nonlocality is a better choice to obtain more accurate results.

Facet separation for disjunctive constraints with network flow representation

We present a novel algorithm for separating facet-inducing inequalities for the convex-hull of the union of polytopes representing a disjunctive constraint of special structure. It is required that the union of polytopes admit a certain network flow representation. The algorithm is based on a new, graph theoretic characterization of the facets of the convex-hull. Moreover, we characterize the family of polytopes that are representable by the networks under consideration. We demonstrate the effectiveness of our approach by computational results on a set of benchmark problems.

Privacy-preserving coordination of power and transportation networks using spatiotemporal GAT for predicting EV charging demands

The gradual replacement of conventional-fuel vehicles by electric vehicles (EVs) in recent years provides a growing incentive for the collaborative optimization of power distribution networks (PDNs) and urban transportation networks (UTNs). However, the implementation of a centralized optimization model for PDNs and UTNs is currently unrealistic due to the requirement for establishing information privacy barriers between the two independently operated networks. The present work proposes a predict-then-optimize (PTO) framework that combines Spatiotemporal Graph Attention Network (STGAT) with enhanced queueing theory to achieve accurate prediction of EV charging demands. Building upon this, it efficiently coordinates optimization between the PDN and UTN, while preserving the information privacy of both independently operated networks. Specifically, the proposed STGAT model predicts vehicle flow by simultaneously exploiting the dynamic temporal and spatial dependencies in the historical traffic data of the target UTN. It then converts the predicted flow into spatiotemporal EV charging demands using an enhanced queuing model that considers the service capacity constraints of charging stations (CSs) and the behavior of EV users. Subsequently, the predicted EV charging demands are integrated into a multi-period PDN scheduling model. The results of numerical computations based on an IEEE 33-bus PDN and real-world traffic flow datasets demonstrate that the scheduling results provided by the proposed approach differ by only 0.5% compared to results obtained when applying actual EV charging demands.

A choice-based approach to dynamic capacitated multi-item lot sizing with demand uncertainty

With the purpose of planning and implementing pricing decisions on a tactical level as well as production decisions on an operational level, we consider – in an integrated form – the capacitated multi-item lot sizing problem with uncertain item demands and price-dependent discrete choice demand. The model is embedded into an overarching rolling horizon procedure allowing for adaptations to changes in demand and cost parameters. We first formulate the static problem version as a nonlinear mathematical program with underlying multinomial logit demand and subsequently linearize it to make it viable for mathematical programming solvers. Uncertainty of demands is taken into account by Monte Carlo simulation. More specifically, we generate random demand scenarios and utilize them as input data for the sample average approximation problem version. We further endow the problem setting with possibilities to incorporate pricing policy requirements such as restricting the number of price adaptations or defining periods without price adaptations. Overall, the developed approach yields a powerful tool for balancing item demands via pricing in a way favorable for adhering to available production capacities and thereby striking a balance between revenues and costs. Computational results confirm that adapting prices to time-dependent demand and cost parameters is exploited effectively to maintain a deliberately controlled production environment. Moreover, the integrated pricing and production setting allows to study the effect of pricing policy restrictions and demand uncertainties upon attainable profits.

Uncovering a general oxidation model of nitrogen-containing oxidant in N-heterocyclic carbene (NHC) catalyzed oxidative reactions of aldehydes

Predicting how oxidants interact with reactive partners to alter the oxidation mechanism is a significant challenge in carbene catalysis. In this study, we investigated several examples to address this issue. Using density functional theory (DFT), we explored N-heterocyclic carbene (NHC)-catalyzed oxidative [2 + 4] annulations of aliphatic aldehydes with α,β-unsaturated ketones, focusing on the role of nitrogen-containing oxidant. Our computational results reveal that a hydrogen-bonding bridge framework, formed during oxidation, is crucial for facilitating π···π stacking interactions between the oxidant and the NHC catalyst. These interactions significantly lower the oxidation energy barrier, enabling a facile hydride transfer. This mechanism was validated across other reactions involving different nitrogen-containing oxidants. Frontier molecular orbital (FMO) analysis demonstrates how the NHC catalyst lowers the cycloaddition energy barrier by altering the orbital overlap from shoulder-to-head to head-to-head. Additionally, this elucidates the origin of stereoselectivity by highlighting energy differences between two reacting components at cycloaddition transition states. The nucleophilic index further predicts the preferred ketone attack site. This work advances our understanding of oxidation mechanisms involving nitrogen-containing oxidants and offers valuable insights for designing potent organic oxidants in organocatalytic oxidative reactions.

Solvent polarity-driven modulation of excited states: A DFT and spectroscopic analysis

The relationship between the photophysical properties of N,N,N’,N’-tetra-p-tolyl-benzidine (TTB) and [1,4-bis[2-[4-[N,N-di(p-tolyl)amino]phenyl]vinyl]benzene (DSB) molecules and solvent polarity was explored through steady-state spectroscopy, femtosecond transient absorption spectroscopy, and quantum chemical calculations. Computational results and steady-state spectra reveal that the lowest singlet excited states of TTB and DSB are primarily characterized by localized excited (LE) states in nonpolar cyclohexane (CHX), whereas intramolecular charge transfer (ICT) components predominate in highly polar acetonitrile (ACN). Compared to TTB, the excited-state potential of DSB demonstrates a heightened sensitivity to solvent polarity, exhibiting larger dipole moments due to enhanced electron transfer enabled by the incorporation of styrene groups. Ultrafast femtosecond transient absorption spectroscopy distinctly shows the transition from LE states in nonpolar CHX to ICT states in highly polar ACN. The deactivation mechanisms were further elucidated to understand how solvent polarity modulates excited states and high quantum yields, providing valuable insights for the design and application of photophysical materials.

Two-set inequalities for the binary knapsack polyhedra

This paper presents two-set inequalities, a class of valid inequalities for knapsack and multiple knapsack problems. Two-set inequalities are generated from two arbitrary sets of variables from a knapsack constraint. This class of cutting planes is not a traditional type of lifting since a valid inequality over a restricted space is not required to start. Furthermore, they cannot be derived using any existing lifting technique. The paper presents a quadratic algorithm to efficiently generate many two-set inequalities. Conditions for facet-defining two-set inequalities are also derived. Computational experiments tested these inequalities as pre-processing cuts versus CPLEX, a high-performance mathematical programming solver, at default settings. Overall, two-set inequalities reduced the time to solve some benchmark multiple knapsack instances to up to 80%. Computational results also showed the potential of this new class of cutting planes to solve computationally challenging binary integer programs.

Enhanced corrosion inhibition performance of 5-amino-3‑bromo-1-methylindazole on copper in sulfuric acid environments

The corrosion inhibitor 5-amino-3‑bromo-1-methylindazole (ABMI) with multiple substituents can effectively protect the copper substrate. According to the electrochemical experiment results, at 298 K, 3 mM ABMI may suppress copper corrosion by 92.1 %. Furthermore, going from 298 K to 308 K raises the temperature at which 3 mM ABMI may continue to suppress corrosion with an efficiency exceeding 90 %. The weight loss test, SEM, AFM, and XRD data all reveal that the presence of ABMI efficiently prevents the corrosion media from dissolving the copper substrate. The ΔGads0 value of ABMI is −32.97 kJ/mol, demonstrating that it works on the metal/solution interface through physical adsorption and chemisorption. The results of molecular dynamics modeling and quantum chemical computation show that ABMI adsorbs to the metal superficies in a nearly parallel way, minimizing the exposure area among the metal superficies with the medium with corrosive substances and providing the best possible protection for copper.

Linamarin Binding to Human Serum Albumin. A Spectroscopic and Molecular Docking Approach

AbstractThe interaction between linamarin (LIN), a cyanogenic glycoside, and human serum albumin (HSA) was studied by multiple spectroscopic techniques and molecular docking simulation. All measurements were performed under physiological conditions. The obtained results (including the binding constants, effective quenching constant and a number of binding sites) showed that the complex of HSA‐LIN is formed. The values of Stern‐Volmer constants (6.70×103, 5.53×103 and 1.95×103) indicate that fluorescence quenching of HSA was static. Results of site marker experiments showed that the binding site of LIN is mainly located in site I (subdomain IIA) of HSA. The thermodynamic parameters showed that binding process occurs spontaneously through hydrophobic interactions. Molecular docking results are in good agreement with experimental data. Furthermore, computational results revealed LIN binds in the cavity of TRP 214, that is, subdomain IIA (site I) of HSA. This comprehensive study provides a deeper insight into ligand binding in HSA which may be useful in drug design and pharmacology.

Numerical investigation on secondary injection and thrust vector control in a planar double divergent nozzle

In this work, the performance of secondary injection thrust vector control of an altitude adaptive planar double divergent supersonic nozzle is numerically investigated. The compressible turbulent flow is solved using the kT−kL−ω transition-sensitive eddy-viscosity model. An analytical model to predict the separation distance and penetration height due to secondary fluid injection is developed based on the blunt-body theory, and it shows good agreement with the numerical estimation. The computational results indicate that injection pressure, injector location and injection angle significantly impact the thrust vector control performance. The core flow is disrupted by the momentum injection from the secondary fluid, causing the flow field structure to become asymmetrical. The wall pressure imbalance between the upper and lower nozzle increases as the secondary jet pressure elevates. Further, the thrust vectoring amplification factor is improved when the injector is placed downstream near the outlet since the shock reflection is circumvented. Indeed, that resulted in the generation of a large lateral thrust force. Most importantly, for a high injector slot angle, the primary downstream vortex disappears, and a strong secondary upstream vortex is generated, which shifts the primary upstream vortex opposite to the core flow, subsequently the shock separation is advanced. In addition, a secondary injector fitted near the exit with high inclination angles and injection pressure generated a lateral thrust of 20%.

Graphene with suitable-size nitrogen-doped cavity being an excellent photocatalyst for proton-coupled electron transfer in water splitting

Aiming to attain porous carbon nitride photocatalysts with high specific surface area, abundant active sites, broad absorption range and effective electron-hole separation, we remove carbon rings from graphene and replace all the edge carbon atoms of the cavity with nitrogen atoms. The accurate electronic structures and exciton properties of the proposed materials are revealed by the ab initio many-body Green's function theory. Computational results show that the absorption of the designed materials can cover both the visible and the near-infrared light region. The exciton binding energies of the materials are one order of magnitude lower than those of the typical two-dimensional photocatalyst graphitic carbon nitride. Due to the formation of hydrogen bonds between pyridinic nitrogen atoms and water molecules during water splitting, the key excited-state proton-coupled electron transfer reactions are barrierless. These findings could serve as guidelines for the realization of high-performance metal-free two-dimensional photocatalysts.

Study on the Rules of Ground Settlement and Pipeline Deformation Considering the Combined Effects of Pipeline Damage Leakage and Shield Tunneling Construction

A pipeline with long-term “hidden leakage” will greatly reduce the stability of the ground between the pipeline and tunnel in the process of tunneling through existing pipelines in unsaturated soil. Excessive settlement of the surrounding strata and pipelines can occur when the shield excavation face approaches below a pipeline, which can lead to engineering accidents. This study is based on a self-developed model experimental system for tunneling through an existing pipeline with a double-line tunnel shield. The ground settlement and pipeline deformation caused by shield construction with small-scale and no leakages are investigated. An experimental study is conducted and the accuracy of the results is verified through a comparison with theoretical solutions. The results demonstrate that there is a significant increase in ground settlement and pipeline deformation under the influence of leakage water. It is also determined that the displacement field generated by the excavation of a double-line tunnel is not simply a superposition of the displacement field generated by the excavation of a single-line tunnel. The repeated disturbances caused by the excavation of a double-line tunnel significantly influences the redistribution of the displacement field. Additionally, a three-dimensional (3D) model of shield construction considering the influence of pipeline leakage is established. This study discusses the ground settlement and pipeline deformation patterns caused by changes in the vertical and horizontal leakage diffusion ranges. The computational results indicate that the diffusion depth of a leakage is the primary factor controlling the extent of settlement.

An adaptive shuffled frog-leaping algorithm for flexible flow shop scheduling problem with batch processing machines

Batch Processing Machines (BPM) and transportation are seldom studied simultaneously in Flexible Flow Shop. In this study, Flexible Flow Shop Scheduling Problem (FFSP) with BPM at the last stage and transportation is considered and an adaptive shuffled frog-leaping algorithm (ASFLA) is proposed to minimize makespan. To produce high-quality solutions, a heuristic is employed to produce initial solution, two groups are formed by using all memeplexes, then an adaptive memeplex search is implemented, in which the number of searches is dynamically determined by the quality of the memeplex, an adaptive group search is also conducted by exchanging memeplexes or supporting of the worse memeplex. A novel population shuffling and the worst memeplex elimination are proposed. A number of computational experiments are executed to test the new strategies and performances of ASFLA. Computational results demonstrate that new strategies are effective and ASFLA is a very competitive algorithm for FFSP with BPM and transportation.

Recording provenance of workflow runs with RO-Crate.

Recording the provenance of scientific computation results is key to the support of traceability, reproducibility and quality assessment of data products. Several data models have been explored to address this need, providing representations of workflow plans and their executions as well as means of packaging the resulting information for archiving and sharing. However, existing approaches tend to lack interoperable adoption across workflow management systems. In this work we present Workflow Run RO-Crate, an extension of RO-Crate (Research Object Crate) and Schema.org to capture the provenance of the execution of computational workflows at different levels of granularity and bundle together all their associated objects (inputs, outputs, code, etc.). The model is supported by a diverse, open community that runs regular meetings, discussing development, maintenance and adoption aspects. Workflow Run RO-Crate is already implemented by several workflow management systems, allowing interoperable comparisons between workflow runs from heterogeneous systems. We describe the model, its alignment to standards such as W3C PROV, and its implementation in six workflow systems. Finally, we illustrate the application of Workflow Run RO-Crate in two use cases of machine learning in the digital image analysis domain.

Hydrogen production mechanism and catalytic productivity of Ni-X@g-C3N4 (X = precious and non-precious promoter metals) catalysts from KBH4 hydrolysis under stress loading and atmospheric pressure: Experimental analysis and molecular dynamics approach

In this study, the pressure effect of Ni-based catalysts added a second promoter metal to increase of catalyst performance supported a graphite carbon nitride (g-C3N4) monolayer on hydrogen release mechanisms from potassium boron hydride (KBH4) hydrolysis was investigated using molecular dynamics (MD) method based on tight-binding density functional theory (DFT). The use of the various promoters, such as transition metals (X = Cu, Ta and W) and noble metals (X = Pd, Pt and Rh) with applying a high external pressure was investigated to understand the role on catalytic performance of the Ni-based catalysts under stress loading. The g-C3N4 monolayer doped with Ni-X nano-catalysts was used for efficient H2 release from KBH4 hydrolysis. The computational results show that the number of H2 shows more increment with MD time for NiW and NiRh catalysts than other NiTa and NiCu (transition metals) and NiPd and NiPt (noble metals) under 0 GPa pressure. On the other hand, a notable increase in H2 amount is seen only NiCu and NiRh catalysts under 50 GPa. Also, the mechanism of the H2 production reaction from KBH4 hydrolysis of g-C3N4 doped NiCo catalysts was clarified. High-performance cost metal catalysts such as NiCo was investigated as both experimentally and modeling under atmospheric pressure to enhance its commercial application value. Some experimental applications and analyzes were also performed to measure the accuracy of the modeling for the relevant molecular groups in the system.

Study of the electrospun PVDF fibrous membrane in capturing particulate matters in smoke by the synergy between GO and CNWs

The filtration capability can be effectively adjusted by involving the incorporation of fillers into filter materials. Here, we present a promising filter material for capturing particulate matters in smoke, a polyvinylidene fluoride (PVDF) fibrous membrane modified by cellulose nanowhisker (CNWs) and graphene oxide (GO), which was prepared by a facile electrospinning method. GO with oxygen-containing groups can improve the capability of capturing particle owing to its excellent adsorption performance. CNWs with highly ordered crystalline regions can alter the dimension and properties of PVDF fibers. The synergistic effect of GO and CNWs enabled uniform fiber diameter, higher porosity, and better filtration property as compared with that of pristine PVDF membranes. Experimental results demonstrated a significant improvement in the filtration efficiency of PVDF fibrous membranes after blending with GO and CNWs. The filtration data showed that the filtration efficiency (95.58%) of GO/CNWs/PVDF membrane was higher than that (87.68%) of CNWs/PVDF membrane and that (86.36%) of PVDF membrane. The reusability for capturing pollutants showed that the fibrous membrane could keep a certain filtration capability (93.85%) after 5 cycles. Computational results suggested there was an interaction between GO and smoke pollutants (monoterpene) and the addition of GO play an effect on the filtration efficiency of fibrous membranes. These results showed that GO/CNWs/PVDF fibrous membranes was ideal filter materials for air pollutant.