Analytical Modeling Approach Research Articles

A comparative study of thermodynamic modeling and experimental measurement of precipitation titration curves for single- and multi-component sulfate systems

The current study is focused on the thermodynamic modeling and experimental measurement of metal hydroxide precipitation titration curves for the single- and multi-component sulfate systems. The systematic analytical model is developed based on Bromley-Zemaitis's theory and H. E. Wirth's theory to accurately predict the precipitation behavior of sulfate systems under different operating conditions and to simulate the precipitation titration curve. The titration curves established using the analytical model are compared with the curves built using the numerical mixed-solvent electrolyte model provided in OLI software along with the experimental measurement. The results demonstrate a good agreement between the analytical model, numerical model, and experimental approach while unveiling the limitations of the developed analytical model such as the disregard of multi-species ions, constant solution density, and constant water activity. The effect of three key operating parameters, namely initial solution pH, initial metal ion concentration, and reaction temperature, on the precipitation behaviors is investigated with emphasis on the ion interaction, precipitation pH, the amount of precipitant required, and species equilibrium.

A State-of-the-Science Review on High-Resolution Metabolomics Application in Air Pollution Health Research: Current Progress, Analytical Challenges, and Recommendations for Future Direction.

Understanding the mechanistic basis of air pollution toxicity is dependent on accurately characterizing both exposure and biological responses. Untargeted metabolomics, an analysis of small-molecule metabolic phenotypes, may offer improved estimation of exposures and corresponding health responses to complex environmental mixtures such as air pollution. The field remains nascent, however, with questions concerning the coherence and generalizability of findings across studies, study designs and analytical platforms. We aimed to review the state of air pollution research from studies using untargeted high-resolution metabolomics (HRM), highlight the areas of concordance and dissimilarity in methodological approaches and reported findings, and discuss a path forward for future use of this analytical platform in air pollution research. We conducted a state-of-the-science review to a) summarize recent research of air pollution studies using untargeted metabolomics and b) identify gaps in the peer-reviewed literature and opportunities for addressing these gaps in future designs. We screened articles published within Pubmed and Web of Science between 1 January 2005 and 31 March 2022. Two reviewers independently screened 2,065 abstracts, with discrepancies resolved by a third reviewer. We identified 47 articles that applied untargeted metabolomics on serum, plasma, whole blood, urine, saliva, or other biospecimens to investigate the impact of air pollution exposures on the human metabolome. Eight hundred sixteen unique features confirmed with level-1 or -2 evidence were reported to be associated with at least one or more air pollutants. Hypoxanthine, histidine, serine, aspartate, and glutamate were among the 35 metabolites consistently exhibiting associations with multiple air pollutants in at least 5 independent studies. Oxidative stress and inflammation-related pathways-including glycerophospholipid metabolism, pyrimidine metabolism, methionine and cysteine metabolism, tyrosine metabolism, and tryptophan metabolism-were the most commonly perturbed pathways reported in of studies. More than 80% of the reported features were not chemically annotated, limiting the interpretability and generalizability of the findings. Numerous investigations have demonstrated the feasibility of using untargeted metabolomics as a platform linking exposure to internal dose and biological response. Our review of the 47 existing untargeted HRM-air pollution studies points to an underlying coherence and consistency across a range of sample analytical quantitation methods, extraction algorithms, and statistical modeling approaches. Future directions should focus on validation of these findings via hypothesis-driven protocols and technical advances in metabolic annotation and quantification. https://doi.org/10.1289/EHP11851.

Research on the formation mechanism of research leadership relations: An exponential random graph model analysis approach

Research on the formation mechanism of research leadership relations: An exponential random graph model analysis approach

Modeling and performance analysis of elastostatic stiffness of kinematically redundant parallel mechanisms

An analytical elastostatic stiffness modeling approach for kinematically redundant parallel mechanisms (KR-PMs) according to screw theory and the second theorem of Castigliano is proposed. The 2-UPR/PRPU and 2-PUPR/PRPU KR-PMs are used as two examples of KR-PMs to validate the precision of the proposed approach. The relative error is less than 1.55% when the theoretical model is compared to the FEA model. The PM’s stiffness performance is assessed using the minimum linear displacement stiffness performance index, which is based on the theoretical model. By integrating Particle Swarm Optimization (PSO) with polynomial fitting technology, an analytical mapping model of the response surface between the optimal actuating distances and the moving platform (MP)’s given position and orientation is established. It is demonstrated that 2-UPR/PRPU and 2-PUPR/PRPU KR-PMs can significantly enhance the stiffness performance when compared to the stiffness performance of 2-UPR/RPU PM.

Designing climate policy mixes: Analytical and energy system modeling approaches

A matter of debate in climate policy is whether lawmakers should rely on carbon pricing or regulations, such as low-carbon standards, to reach emission reduction goals. Past research showed that pricing is more cost-effective. However, previous work studied the two policies when implemented separately, in effect comparing two policy extremes. In contrast, we explore the full spectrum of climate policy mixes that include both types of policies but vary in how much they rely on each. We do this both analytically by extending previous theory and numerically with two energy system models. In line with past work, increasing reliance on pricing increases the cost-effectiveness of the policy mix. However, we show that this benefit exhibits diminishing marginal returns. Thus the gain in cost-effectiveness from complementing stringent standards with modest pricing is relatively large. Our results show that relying on pricing for 20% of emission reductions (and on a standard for 80%) reduces costs by 32%–57% compared to a standard-only approach. Importantly, trading off more of the standard for pricing delivers smaller and smaller gains in cost-effectiveness. For example, a policy mix that relies on each policy for 50% of emission reductions decreases costs by 60%–81%, which is already 71%–88% as cost-effective as the theoretically most cost-effective pricing-only policy.

Coordinate System Invariant Formulation of Fractional‐Dimensional Child‐Langmuir Law for a Rough Cathode

AbstractThis work presents an exact closed‐form analytical model of the space charge limited (SCL) current density for planar, cylindrical, and spherical geometries in fractional dimensional spaces (Fα) where α represents the fractional dimensions having a range 0 < α ⩽ 1. Decreasing value of α shows an increasing degree of surface roughness. This analytical model approaches Langmuir–Blodgett equations for sufficiently close anode (Ra) and cathode (Rc) radii for integer dimensions (α = 1). To calculate SCL current density for any geometry, variational calculus (VC) is used to derive the differential equations in fractional (α) dimensions. The effect of electrode radius ratios on space charge limited current is investigated here considering the surface roughness.

Surrogate infection model predicts optimal alveolar macrophage number for clearance of Aspergillus fumigatus infections

The immune system has to fight off hundreds of microbial invaders every day, such as the human-pathogenic fungus Aspergillus fumigatus. The fungal conidia can reach the lower respiratory tract, swell and form hyphae within six hours causing life-threatening invasive aspergillosis. Invading pathogens are continuously recognized and eliminated by alveolar macrophages (AM). Their number plays an essential role, but remains controversial with measurements varying by a factor greater than ten for the human lung. We here investigate the impact of the AM number on the clearance of A. fumigatus conidia in humans and mice using analytical and numerical modeling approaches. A three-dimensional to-scale hybrid agent-based model (hABM) of the human and murine alveolus allowed us to simulate millions of virtual infection scenarios, and to gain quantitative insights into the infection dynamics for varying AM numbers and infection doses. Since hABM simulations are computationally expensive, we derived and trained an analytical surrogate infection model on the large dataset of numerical simulations. This enables reducing the number of hABM simulations while still providing (i) accurate and immediate predictions on infection progression, (ii) quantitative hypotheses on the infection dynamics under healthy and immunocompromised conditions, and (iii) optimal AM numbers for combating A. fumigatus infections in humans and mice.

Prioritization of Sub-watersheds for the Categorization of Surface Runoff and Sediment Production Rate Based on Geo-spatial Modeling and PCA Approach: A Case from Upper Beas River, Himachal Pradesh, India

Abstract Studying geo-morphometric parameters using Remote Sensing (RS) and Geographic Information System (GIS) tools is crucial to routing runoff and remaining hydrological processes. A geo-spatial model and principal component analysis (PCA) approach are used in this study to prioritize sub-watersheds of the upper Beas river up to Pandoh dam. Dendritic drainage patterns throughout its sub-watersheds characterized the 6th-order Beas river. The sub-watersheds show a lithological uniformity that indicates that the entire watershed has structurally impermeable materials at both surface and sub-surface levels. Moreover, the aerial and relief aspects of the sub-watershed indicate fine drainage textures, steep slopes, immediate peak flows, a hydrograph with multiple peaks, and a low concentration time. In other words, the sub-watershed may not be able to manage flash floods during the storm period. Surface runoff and sediment production rates (SPR) were estimated in the present study ranged from 3.576 - 5.240 sq. km-cm/sq.km and 0.101 - 0.234 ha-m/100sq.km/year, respectively. Finally, the study concluded that the sub-watersheds in the upper regions produced high runoff and sediments, usually carried into the mainstream. Further, the PCA technique was applied to find the redundant morphometric parameters and then the same results were utilized to determine the effective way to prioritize the watershed. The present study will serve as a basis for developing appropriate policies and practices for peak flooding and promoting the sustainability of the watershed.

High-fidelity analytical modeling of asymmetric CFRP composites using Reissner–Mindlin theory and hygroscopic degradation

Multi-stable carbon fiber-reinforced composites with asymmetric ply layouts have shown promising potential for creating multi-functional structural systems. To design and analyze these complex composites, high-fidelity and computationally efficient analytical models are crucial. To this end, Hyer and Dano formulated the first model four decades ago based on classical lamination theory (CLT). Surprisingly, despite many follow-up studies to refine this analytical approach, current models still follow the same fundamental ingredients used in Hyer and Dano’s original work. As a result, they all inherited the same limitations. For example, they ignore the interlaminar stresses and lack a rigorously calibrated hygroscopic term. To overcome these limitations, we propose a new analytical modeling approach by adopting the Reissner–Mindlin theory and hygroscopic degradation. This new model introduces in-plane rotations as two additional degrees of freedom and a combined expansion coefficient for the epoxy matrix materials. Compared to finite element simulations and experiment data, the new model can estimate the interlaminar stress reasonably well (especially regarding its concentration near the edges) and predict the laminates’ external shape more accurately than an equivalent Hyer’s model. The new model can also accurately predict the reduction in the laminate’s curvature and snap-through force in different design configurations, as well as their linear correlation to the moisture content levels. Overall, the results of this study present a fundamental advancement in the analytical modeling of asymmetric multi-stable composite laminates, offering a broad and versatile foundation for designing and analyzing the next generation of multi-functional composite structures.

A linear wake expansion function for the double‐Gaussian analytical wake model

AbstractThe double‐Gaussian (DG) approach for analytical wake modeling leads to a better understanding of the wake transition mechanism within a full‐wake region behind a non‐yawed horizontal‐axis wind turbine (HAWT). To date, a key parameter of the wake expansion in the DG model still has yet to be defined explicitly instead of tuning, thus limiting its usability for practical applications. The present work aims to overcome this limitation by proposing a simple linear wake expansion function for the DG model constructed from the existing parameters based on the conservation of mass and momentum. Considering the physical and statistical approaches, the proposed function is specifically intended to approximate the wake expansion downstream of a non‐yawed HAWT under turbulence inflow. Seven case studies from wind tunnel measurements and large eddy simulations under different inflow conditions were used to examine the effectiveness of the proposed function. In general, the evaluation results in the present study show the effectiveness of the proposed expansion function for the DG wake model to predict the wake expansion and its recovery behind a non‐yawed HAWT without a prior adjustment or tuning of the wake expansion parameter.

A molecular dynamics study of water confined in between two graphene sheets under compression

Several studies have demonstrated interest in creating surfaces with improved water interaction and adaptive properties because the behavior of water confined at the nanoscale plays a significant role in the synthesis of materials for technological applications. Remarkably, confinement at the nanoscale significantly modifies the characteristics of water. We determine the phase diagram of water contained by graphene stack sheets in slab form, at T = 300 K, and for a constant pressure using molecular dynamics simulations. We discover that, as shown in the simulation, water can exist in both the liquid and vapor phases depending on the confining geometry and compressibility ratio. We also pay attention to how stable the interacting liquid is in relation to the pressure of compression that is perpendicular to the graphene sheets. To build this system and analyze its surface interface properties, we also used analytical and electronic scale modeling approaches. The impact of nanoconfinement on internal pressure may be seen in water, and this can be used to create interfacial materials for the creation of environmentally friendly solar cell materials. Our research highlights the intricate, seemingly random behavior of nanoconfined water—behavior that is difficult for graphene to understand. The results obtained offer crucial direction for system design and configuration of materials at the graphene/water interface that can be utilized as a benchmark for other future designs.

Design of Rural Human Settlement Unit with the Integration of Production-Living-Ecology of China Based on Dynamic Emergy Analysis

It is of great theoretical and practical significance to optimize and improve the design of rural human settlement units through system ecology analysis based on emergy evaluation indices. From the perspective of system ecology, the rural living environment system is multivariate and complicated, with strong correlations and obscure boundaries between levels. Therefore, the definition of a rural human settlement unit in China is proposed in this research and can be divided into three scales: the microcosmic scale, mesoscale, and macroscopic scale. This research adopted a new method for the design of rural human settlement units by adopting emergy as a common dimension in order to solve the problem of dimensionality disunity between resource environment elements and society economy elements. Through the establishment of the static emergy analysis model and dynamic emergy prediction model, qualitative and quantitative analysis approaches of the rural human settlement unit were combined. According to the design orientations of industry-invigorative, environment-friendly, and ecology-balanced, corresponding with production-living-ecology integration, emergy evaluation indices including the emergy self-sufficiency ratio, emergy investment ratio, net emergy yield ratio, environmental load ratio, and emergy sustainable indices were calculated and predicted by means of system dynamics simulation. The dynamic emergy prediction results showed that the emergy self-sufficiency ratio and emergy sustainable indices basically presented a decreasing tendency, from 0.34 to 0.15 and from 0.76 to 0.57, respectively, with the passage of time; the values of the emergy investment ratio, net emergy yield ratio, and environmental load ratio basically presented an increasing tendency, from 2.13 to 2.78, from 1.66 to 2.12, and from 2.23 to 3.61, respectively, with the passage of time. In practice, the evaluation method based on the emergy analysis of the technical strategies and spatial arrangements of the rural human settlement unit can provide data support for designing standards, planning guidelines, and creating constructional instructions for the rural living environment of China.

Analytical prediction of stress and strain in adhesive tube-to-tube joints under thermal expansion/contraction

ABSTRACT Adhesive joints are widely applied and studied for various industrial applications. The interest in adhesive joints has expanded to include heating, ventilation, air conditioning, and refrigeration (HVAC&R) systems having a significant number of joints employed for manufacturing. This study investigates an analytical modeling approach for predicting joint stress and strain distribution under static loading with thermal strain. A review of modeling techniques identified the need to develop a joint analytical model under loading conditions representative of HVAC&R applications. The details of the model, governing equations, assumptions, boundary conditions, and solution techniques are first reported. The model is validated via comparison to existing results before performing parametric studies to provide insights on the influences of thermal expansion and inner tube pressure on possible failure. It is found that the joint overlap length plays an important role in stress distribution, while the adhesive thickness has less impact. Overall, the results indicate that static loading failure is not likely a concern for joints in HVAC&R systems, but the thermal strain and stress induced by temperature fluctuations must be carefully considered. This modeling effort establishes a framework that can be used to generate criteria and instructions on designing adhesive joints across different HVAC&R

Analytical approach for modeling and simulation of photonic crystal fiber based on low effective material loss

COMSOL Multiphysics simulation software has been used to create a hexagonal photonic crystal fiber (H-PCF) with hexagonal cladding and a rotating hexa elliptical shape core. The hexagonal photonic crystal fiber (H-PCF) fiber is built on five layers of circular air holes, and it is suitable for telecommunication applications especially optical fiber communication in the terahertz (THz) frequency range. The hexagonal photonic crystal fiber (H-PCF) is designed to have an ultra-low effective material loss (EML), a higher core power fraction, a bigger effective area, and reduced confinement loss. The smallest effective material loss from the proposed hexagonal photonic crystal fiber (H-PCF) is 0.00689 cm−1, with a better core power fraction of 82%, less confinement loss of 3.45 × 10–14 cm−1 and a better effective area of 3.65 × 10–4 m2 is achieved at one terahertz (THz) waveguide region. Furthermore, using the features of the V-Parameter, our developed hexagonal photonic crystal fiber (H-PCF) fiber reveals an optical waveguide with one mode throughout a frequency range of terahertz (THz) wave area. So, it has been said that our hexagonal photonic crystal fiber (H-PCF) structure will be highly beneficial for optical fiber communications applications in the THz frequency range.

On the utilization of dedicated bus lanes for pooled ride-hailing services

Ride-sourcing platforms, among other solution services, offer convenience and flexibility when it comes to pick-up/drop-off time and location. Similarly, ride-splitting renders itself as an extension of ride-sourcing where platform users agree to share their rides in return for a reduced fare yet possibly a longer travel time. Despite the numerous advantages that sharing introduced to the platform operator by reducing the fleet size necessary to serve demand levels, e-hailing is still overall negatively impacting traffic performance in urban spaces. This is partially due to the current tendency of users to favor solo over shared rides. This paper aims to use aggregate traffic flow models to put forward a network space redistribution policy that has the potential to reduce total delays of the different mode users in the network. Accordingly, we investigate the solo-pool demand split that minimizes the total Passenger Hours Traveled for all network commuters in the event where shared rides are allowed to use underutilized bus lanes. As a result, the choice to share is associated with an inevitable additional detour distance but with a lower-than-expected trip time compared to standard scenarios where the whole fleet utilizes the same network space. In this paper, we present an analytical macroscopic modeling approach to evaluate equilibrium solutions between network supply and multi-modal demand. By resorting to a numerical example of the model, we show that the optimal strategy that minimizes delays for multi-modal transport users occurs when only a fraction of the pooling vehicles uses the dedicated bus lanes. This fraction is dependent on the distribution of space and the value of demand for private vehicles, buses, and ride-hailing services.

Resilient sustainable investment in digital education technology: A stakeholder-centric decision support model under uncertainty

Investment in education technology (EdTech) is a complex decision problem for universities during the post-Covid era. With the objective to assess the quality and adoptability of education supply chain, a novel analytical evaluation model approach is proposed, based on quality function deployment and combinative distance-based assessment. To deal with uncertainty in the evaluation process, fuzzy theory is integrated into the model. To establish the house of quality matrix, technology-based stakeholders' requirements were identified and classified in four dimensions: economic and financial, technology adoption, sustainability, competencies. Moreover, nine supplier criteria were assumed. Based on expert evaluations, the results suggest that financial credit and supplier collaboration are the most prominent attributes to evaluate suppliers, while environmental commitment is sorted as the least important criterion. The results reveal that the three dominant suppliers, which provide the best response to the identified criteria, are providers of cloud service technology.

Bricolage as an effective tool for the survival of owner-managed SMEs during crises

This study analyzes how the resources and capabilities of the owner-manager influence the firm’s capacity to survive during crises. We conceptualize that only the deliberate use of available resources (bricolage) can enhance this capacity, and that “making-do” behaviors mediate the influence of the owner’s social and human resources on the firm's capacity to survive crises. Based on a sample of 462 Chilean owner-managed small and medium enterprises (SME), we test our hypotheses using a complementary partial least squares-structural equation modeling (PLS-SEM) and fuzzy set-qualitative comparative analysis (fsQCA) approach. The results indicate that when founders deliberatively use their social and cognitive resources, they enhance the firm’s capacity to survive in crisis environments. The fsQCA results complement these outcomes by showing that low levels of survival capacity are related to low levels of bricolage and founders’ ties.

Development of delay mitigation measures in construction projects: a combined interpretative structural modeling and MICMAC analysis approach

Construction delays are recurrent worldwide, regardless of the type of work, and can result in severe impacts, such as time and cost overruns and conflicts. This work aims to present a methodology to develop mitigation measures for the causes of Delays in Construction Projects (DCPs). Prior works have explored strategies to develop these measures but systematically failed to consider that the interrelationships among causes affect the significance of the impact of each cause. The methodology proposed combines the Interpretative Structural Modelling (ISM) and Matrix Cross Impact Matrix Multiplication (MICMAC) analyses approaches and is grounded on the opinions of construction experts collected during Focus Group Interviews (FGI). First, the critical causes of DCPs are identified. Second, the ISM model is built, representing the interrelationships between the causes and their hierarchy. Third, the MICMAC analysis is performed, revealing the strengths of the relationships among the influencing causes. Fourth, mitigation measures are developed to address the root causes identified in the previous steps, but they are designed to target and mitigate other causes, given their hierarchical relationships, driving power, and levels of dependence. Applying this methodology to the Portuguese context revealed 16 critical causes, which were then hierarchized into six levels of influence. Inadequate bidding and contract award processes and deficient communication between parties were deemed root causes, and 23 measures were put forward to mitigate DCPs. Therefore, this study contributes to the body of knowledge by designing an innovative and practitioner-wise methodology to develop mitigation measures in relation to DCPs and revealing some measures for the Portuguese context.

Actualization of technological interaction managing methods in portside transport systems

Methodological approaches to the assessment of the portside transport and technological system development prospects in terms of interaction management in the “railway station - port” system are being studied. The method of port wagon flow distribution on the basis of combined application of analytical and simulation modeling, probabilistic-statistical and censorological approach is presented. An algorithm for the formation and assessment of the transport process axiom in the “railway station - port” system is formed. The approximations of power functions in the technocenosis of port station parameters are determined. Scientific methods, based on linear and dynamic programming, mass service theory, reliability theory, graph theory, probability theory, simulation modeling, etc. are widely used in the management of traffic flows. To describe the regularities of transport processes, the notions: individual, species, population, etc. are used in CA of the system “railway station - port”. The structural elements of the portside transport system, evaluated by means of CA, are presented in аrticle.

A Topic Modeling and Sentiment Analysis Approach for Benchmarking of Hotels Based on Online Reviews

This paper proposes a methodology that utilizes online reviews for performing competitive and customer-driven benchmarking. The utilization of online reviews may overcome the difficulty of obtaining information about competitors through conventional approaches, such as surveys. A topic modeling method, Latent Dirichlet Allocation (LDA), identifies the essential aspects discussed in the reviews. Combining the identified aspects with sentiment analysis, the best practices may be discovered with respect to each important aspect. In the case study, ten important aspects are identified, i.e., Room Amenities, Parking Area, Food & Beverage, Check-in/out, Fitness & Recreational Facilities, Hospitality, Room Quality, Staying Experience, Design, and Location. Furthermore, adjective words are used to obtain more specific customer needs regarding an aspect. Those customer needs may suggest improvements that hotels may implement, such as reducing the air-conditioner’s noise and improving the rooms’ soundproofing.