Theoretical Modeling Approach Research Articles

The strain hardening of micro-sized face-centered-cubic single crystal metals: A crystal plasticity study

Recent experimental and theoretical studies indicate the “external geometry” and “internal structure” are the controlling factors to characterize the size-dependent plastic flow for micro-sized single crystal metals. i.e., increasing yield strength with decreasing sample size. This paper aims to investigate the strain hardening behavior for micro-sized face-centered-cubic (FCC) metals by employing crystal plasticity approach. The size-dependent dislocation density evolution law incorporates the dimensional parameters of internal structure and external geometry in order to consider the dislocation surface annihilation and dislocation source controlled plastic mechanisms. The current shear yield strength for micro-sized FCC metals is formulated by introducing the dislocation source length in classical anisotropic hardening model of Franciosi type. Combined with the above two aspects, crystal plasticity finite element method is developed to examine the strain hardening behavior of single crystal micro-sized metals during uniaxial compression. The validity of the new theoretical formulation and modeling approach is checked by comparing the simulation results with the experimental results available in literatures. The simulation results indicate that the micro-sized FCC metals have significant size effect. Further studies are performed to evaluate the influences of the initial dislocation density and the number of dislocation sources on strain hardening behavior of micro-sized FCC metals.

Getting the most out of intensive longitudinal data: a methodological review of workload–injury studies

ObjectivesTo systematically identify and qualitatively review the statistical approaches used in prospective cohort studies of team sports that reported intensive longitudinal data (ILD) (>20 observations per athlete) and examined the...

Transport properties of SrCo0.9Nb0.1O3-δ and SrCo0.9Ta0.1O3-δ mixed conductors determined by combined oxygen permeation measurement and phenomenological modeling

Mixed oxide-ion and electron conductors (MIECs) are a scientifically and technologically important class of functional materials for energy conversion and storage. The present work reports a study on transport properties of two well-known MIECs, SrCo0.9Nb0.1O3-δ (SCN) and SrCo0.9Ta0.1O3-δ (SCT), using a combined experimental oxygen permeation measurement and theoretical modeling approach. The results suggest that SCN has a higher oxygen diffusivity, surface oxygen exchange rate constant and oxide-ion conductivity than SCT even though both materials have the same crystal structure. A molecular orbital energy analysis reveals that the slight difference in outer electronic shell configuration between Nb5+ and Ta5+ is responsible for the variance in transport properties.

A Review of Modeling Approaches and Tools for the Off-design Simulation of Organic Rankine Cycle

Organic Rankine Cycles (ORCs) are an effective way to produce electricity from low-grade heat sources, which cannot be effectively obtained using conventional high-temperature Rankine cycles. Due to the lack of available information regarding the real Organic Rankine Cycle units on industrial level, off-design simulation under diversified operating conditions plays a significant role for both the system performance prediction and control strategy design. This paper summarizes the theoretical basis, modeling approaches and tools for ORC off-design simulations. Firstly, a review was conducted on the individual state-of-the-art convective heat transfer correlations and void fraction models. Secondly, different kinds of modeling approaches and simulation tools were proposed, highlighting their relevant characteristics, and were categorized for their specific applications. Moreover, an in-depth analysis of technical challenges related to various applications and focusing on the model accuracy and complexity, computational efficiency, as well as the model compatibility were extensively described and discussed. Finally, the current research trends in this field and the development for further investigations were presented.

Electromagnetic modeling of anisotropic ferrites—Application to microstrip Y-junction circulator design

This paper presents a theoretical tool, which combines a generalized permeability tensor model, a homemade 3D magneto-static solver, and a commercial electromagnetic simulation software Ansys HFSS™ for accurate modeling of ferrite-based devices regardless of their state of magnetization. A magneto-static analysis is carried out to find the internal biasing fields in the ferrite sample. Permeability tensor components are computed using a generalized permeability tensor model. Real and imaginary parts of permeability tensor components are then integrated into the commercial 3D electromagnetic simulation software HFSS retaining the spatial variations of internal biasing fields in the ferrite sample. Frequency domain simulations are done using HFSS. This theoretical modeling approach is validated by comparing the theoretical simulation results with experimental ones in the case of a coaxial line loaded by a magnetized ferrite. Proposed approach is then applied to the design of a microstrip Y-junction circulator. Finally, a demonstration prototype is manufactured in the Low Temperature Co-fired Ceramics technology.

Experimentally validated modeling of a turbo-compression cooling system for power plant waste heat recovery

Waste heat recovery systems utilize exhaust heat from power generation systems to produce mechanical work, provide cooling, or create high temperature thermal energy. One system that provides a cooling effect is the turbo-compression cooling system, which operates by using low-grade waste heat to vaporize a fluid and spin a turbine in a recuperative Rankine cycle. The turbine power is used to directly drive a compressor in a traditional vapor-compression cycle. This study presents a theoretical modeling approach that uses compressor and turbine efficiency maps and a heat exchanger UA scaling methodology to make performance predictions over a range of ambient temperatures and cooling loads. The results of experimental testing for a 250 kWth TCCS showed good correlation (maximum error of 2.0%) for power and cooling cycle mass flow ranges of 0.35 kg s−1–0.5 kg s−1 and 0.65–0.85 kg s−1, respectively. The validated modeling approach was used to predict system performance for a Natural Gas Combined Cycle power plant application.

Quantum-Continuum Simulations of High Power Density Oxide Electrodes for Pseudocapacitive Energy Storage

Pseudocapacitors are energy-storage devices characterized by fast and reversible redox reactions near the surface of an electrode that allows them to store large amounts of energy at fast rates [1]. Much is unknown about these materials due to the complex electrochemical reaction that occurs at the interface between the electrode and solvent. A theoretical modeling approach is developed focusing on ruthenium dioxide (RuO2), a prototypical pseudocapacitive electrode material, for analyzing the electrochemical response of an electrode under realistic conditions in order to identify the factors that control the performance. Electronic-structure methods are used in combination with a self-consistent continuum solvation model to generate a complete dataset of free energies for varying amounts of proton coverage on the surface. The dataset is used in conjunction with a grand-canonical Monte Carlo sampling technique that computes hydrogen-adsorption isotherms and the charge-voltage response of the system. Close agreement is found with experimental results of the RuO2 (110) surface under optimal surface charging conditions [2]. It is found that the intrinsic double-layer contribution represents a small fraction of the overall electrochemical response of the electrode but controls to a large extent the onset of pseudocapacitive reactions by influencing the change in the surface dipole. At variance with RuO2 (110), the double-layer capacitance of RuO2 (100) is found to vary linearly across a significant portion of the voltage range. This range of variation is also well captured by first-principles calculations of the double-layer capacitance for different coverages. The newly developed model provides a widely applicable computational method to help identify novel pseudocapacitive materials. [1] V. Augustyn. P. Simon, and B. Dunn, Energy and Environ. Sci. 7, 1597 (2014) [2] N. Keilbart, Y. Okada, A. Feehan, S. Higai, and I. Dabo, Phys. Rev. B 95, 115423 (2017)

Standard Data-Based Predictive Modeling for Power Consumption in Turning Machining

In the metal cutting industry, power consumption is an important metric in the analysis of energy efficiency since it relates to energy consumption of machine tools. Much of the research has developed predictive models that correlate process planning decisions with power consumption through theoretical and/or experimental modeling approaches. These models are created by using the theory of metal cutting mechanics and Design of Experiments. However, these models may lose their ability to predict results correctly outside the required assumptions and limited experimental conditions. Thus, they cannot accurately reflect a diversity of machining configurations; i.e., selections of machine tool, workpiece, cutting tool, coolant option, and machining operation for producing a part, which a machining shop has operated. This paper proposes a predictive modeling approach based on historical data collected from machine tool operations. The proposed approach can create multiple predictive models for power consumption, which can be applicable to the diverse machining configurations. It can create fine-grained models predictable up to the level of a numerical control program. It uses standard-based data interfaces such as STEP-NC and MTConnect to implement interoperable and comprehensive data representations. This paper also presents a case study to demonstrate the feasibility and effectiveness of the proposed approach.

Advanced Optical Materials : Shedding Light on Excellent Research for 5 Years

<i>Advanced Optical Materials</i> : Shedding Light on Excellent Research for 5 Years

Broadening Horizons – Welcome to Advanced Theory and Simulations

We are proud to present the inaugural issue of our new interdisciplinary premium journal Advanced Theory and Simulations, addressing the growing importance of the development and application of theoretical methods, modeling and simulation approaches in all natural science, medicine and engineering areas. Reflecting the broad scope of the new journal, we are pleased to be supported by the members of a topically and geographically diverse Editorial Advisory Board of leading scientists in their respective fields: Jean-Luc Brédas (Georgia Institute of Technology, Atlanta, USA), Emily Carter (Princeton University, USA), Maytal Caspary Toroker (Technion IIT, Haifa, Israel), Liang Chen (Ningbo Institute of Industrial Technology, Zhejiang, China), Clémence Corminboeuf (Ecole polytechnique fédérale de Lausanne, Switzerland), Bert de Groot (Max Planck Institute for Biophysical Chemistry, Göttingen, Germany), Stefan Grimme (University of Bonn, Germany), Chi-Ok Hwang (Gwangju Institute of Science and Technology, South Korea), Natalie Kalev-Kronik (Hadassah Medical Center, Jerusalem, Israel), Toshihiro Kawakatsu (Tohoku University, Sendai, Japan), Alexei Khokhlov (Moscow State University, Russia), Kurt Kremer (Max Planck Institute for Polymer Research, Mainz, Germany), Leeor Kronik (Weizmann Institute of Science, Rehovoth, Israel), Jürgen Kurths (Potsdam Institute for Climate Impact Research, Germany), Javier Llorca (Madrid Institute for Advanced Studies of Materials, Spain), Jinhu Lu (Research Center for Network Science, Beijing, China), Siewert-Jan Marrink (University of Groningen, The Netherlands), Yifei Mo (University of Maryland, College Park, USA), Rosalba Perna (Stony Brook University, USA), Zhigang Shuai (Tsinghua University, Beijing, China), Berend Smit (University of California, Berkeley, USA), Sean Smith (University of New South Wales, Sydney, Australia), Richard M. W. Wong (National University of Singapore), Xin-Cheng Xie (Peking University, Beijing, China), Yong-Wei Zhang (Institute of High Performance Computing, Singapore). The current first issue already provides a first glimpse at some of the topical range Advanced Theory and Simulations intends to cover, presenting work on semiconductor interfaces, on non-amphiphilic structures, on one-dimensional materials, on the theory of critical distances, or on hydrogen damage protection. We sincerely hope that you enjoy reading this very first issue of the new journal and look forward to receiving soon some of your best research for publication. The Editorial Team of Advanced Theory and Simulations

Modelling the Dynamics of Government Finance on Bond Market Return in Nigeria

This study proposes a theoretical modeling approach for analyzing the impact of government finance on bond market return in Nigeria. The overall result shows that government finance affects not only the rate of return on asset issued by government but also the rate of return on private securities.

Polymorphic uncertainty quantification for stability analysis of fluid saturated soil and earth structures

AbstractNowadays, numerical simulations enable the description of mechanical problems in many application fields, e.g. in soil or solid mechanics. During the process of physical and computational modeling, a lot of theoretical model approaches and geometrical approximations are sources of errors. These can be distinguished into aleatoric (e.g. model parameters) and epistemic (e.g. numerical approximation) uncertainties. In order to get access to a risk assessment, these uncertainties and errors must be captured and quantified. For this aim a new priority program SPP 1886 has been installed by the DFG which focuses on the so called polymorphic uncertainty quantification. In our subproject, which is part of the SPP 1886 (sp12), the focus is driven on quantification and assessment of polymorphic uncertainties in computational simulations of earth structures, especially for fluid‐saturated soils. To describe the strongly coupled solid‐fluid response behavior, the theory of porous media (TPM) will be used and prepared within the framework of the finite element method (FEM) for the numerical solution of initial and boundary value problems [2, 3]. To capture the impacts of different uncertainties on computational results, two promising approaches of analytical and stochastic sensitivity analysis will enhance the deterministic structural analysis [6–8]. A simple consolidation problem already provided a high sensitivity in the computational results towards variation of material parameters and initial values. The variational and probabilistic sensitivity analyses enable to quantify these sensitivities. The variational sensitivities are used as a tool for optimization procedures and capture the impact of different parameters as continuous functions. An advantage is the accurate approximation of the solution space and the efficient computation time, a disadvantage lies in the analytical derivation and algorithmic implementation. In the probabilistic sensitivity analysis from the field of statistics, the expense only increases proportionally to the problems dimension. Instead of a constant value, the model parameters are defined as probability distribution, which provides random values. Thus, a set of solution data is built up by several cycles of the simulation. Different approaches of the Bayes statistics will enable to receive accurate information with just a few simulations. The overall objective is the development of more efficient methods and tools for the sizing of earth structures in the long‐run. (© 2017 Wiley‐VCH Verlag GmbH &amp; Co. KGaA, Weinheim)

Stochastic prediction of burst pressure in composite pressure vessels

The main objective of this research is to predict burst pressure of composite pressure vessels subjected to internal pressure taking into account manufacturing uncertainties. Firstly, first-ply-failure (FPF) of composite pressure vessels with/without liner is studied comparing performance of different failure criteria. Then, burst pressure of the vessels are deterministically predicted using progressive damage modeling based on continuum damage mechanics approach. Both theoretical modeling approaches on predicting FPF and burst pressure are validated using available experimental data. Finally, stochastic modeling is conducted to estimate burst pressure of composite pressure vessels taking into account fiber volume fraction, winding angle and mechanical and strength properties as random parameters resembling manufacturing-induced inconsistencies. Statistical data analysis shows the importance of taking into consideration manufacturing variability.

Quantification of gas phase hydrogen peroxide and methyl peroxide in ambient air: Using atmospheric pressure chemical ionization mass spectrometry with O2−, and O2−(CO2) reagent ions

Instrumentation and ion chemistry are described for the measurement of hydrogen peroxide (H2O2) and methyl peroxide (CH3OOH) in ambient air by chemical ionization mass spectrometry (CIMS). A CIMS, designed and certified for aircraft deployment, was used in this work. The reagent gas was ultrapure air containing 400ppm CO2. The resultant reagent ions, O2− and O2−(CO2), form cluster ions with CH3OOH and H2O2, respectively, and are monitored at 80m/z [O2−(CH3OOH)] and 110m/z [O2− (CO2)(H2O2)]. The CIMS instrument was periodically calibrated using gas-phase standards generated from aqueous solutions. A Carulite-200® catalyst was used to remove peroxides from ambient air to blank the system to account for variations in the ambient air matrix. H2O2 also forms a stable cluster ion with O2− though its calibration behavior was more complex than that for O2−(CO2) in ambient air. The instrument was deployed on the National Center for Atmospheric Research Gulfstream-V aircraft. Representative measurements from the May-June 2012 Deep Convective Clouds and Chemistry experiment spanning altitudes between 0 and 13km over the south-central midwest and southeastern United States are shown. Laboratory experiments, airborne experiments and theoretical molecular modeling approaches were utilized to identify and select reagent ions and to understand the ion-molecule reactions for the formation of peroxide-ion clusters in the ambient air matrix under tropospheric conditions. The analytical viability of a particular ion-molecule adduct was supported by ab-initio molecular orbital calculations.

The necessity of desalination technology for designing and sizing multi-loop aquaponics systems

Providing both fish and plants with optimal environmental conditions is a classical problem in the field of aquaponics. Several studies have tackled this problem by decoupling fish and plant systems. However, in order to achieve both high nutrient levels for the plants and low nutrient and particulate loading in the fish tanks, suspended matter in the aquaculture component needs to be discharged and fertilizer needs to be added to the plants continuously. The present study aims to explore to what degree desalination technology could potentially be used to provide the necessary balance between the two different components based on a theoretical modelling approach using contemporary source material. We suggest how specific desalination engineering approaches can improve the nutrient balances in multi-loop aquaponics systems in order to attain optimal growth conditions for both fish and plants.

Modeling the structure formation process of twin polymerization

Twin polymerization is an elegant technique to synthesize nanostructured organic–inorganic polymers with defined domain sizes of 0.5–3 nm. Although various classes of chemical structures undergoing twin polymerization have been found, the theoretical understanding of the overall twin polymerization process and especially of structure formation of the composite material is still at the beginning. Here, we introduce three different theoretical modeling approaches to investigate and analyze the structure formation process of twin polymerization on different levels of detail. We develop new methods and extend existing ones that range from reactive molecular dynamics simulations to reaction kinetics to reactive bond fluctuation models. We compare the obtained simulation results with experimental and quantum chemical data and find very good to reasonable agreement between theoretical modeling and experimental results. In doing so we achieve detailed insights to the structure formation process of twin polymerization on different length scales.

Disordered Nanohole Patterns in Metal-Insulator Multilayer for Ultra-broadband Light Absorption: Atomic Layer Deposition for Lithography Free Highly repeatable Large Scale Multilayer Growth

In this paper, we demonstrate a facile, lithography free, and large scale compatible fabrication route to synthesize an ultra-broadband wide angle perfect absorber based on metal-insulator-metal-insulator (MIMI) stack design. We first conduct a simulation and theoretical modeling approach to study the impact of different geometries in overall stack absorption. Then, a Pt-Al2O3 multilayer is fabricated using a single atomic layer deposition (ALD) step that offers high repeatability and simplicity in the fabrication step. In the best case, we get an absorption bandwidth (BW) of 600 nm covering a range of 400 nm–1000 nm. A substantial improvement in the absorption BW is attained by incorporating a plasmonic design into the middle Pt layer. Our characterization results demonstrate that the best configuration can have absorption over 0.9 covering a wavelength span of 400 nm–1490 nm with a BW that is 1.8 times broader compared to that of planar design. On the other side, the proposed structure retains its absorption high at angles as wide as 70°. The results presented here can serve as a beacon for future performance enhanced multilayer designs where a simple fabrication step can boost the overall device response without changing its overall thickness and fabrication simplicity.

Iron speciation in peats: Chemical and spectroscopic evidence for the co-occurrence of ferric and ferrous iron in organic complexes and mineral precipitates

The speciation of iron (Fe) in organic matter (OM)-rich environments under in situ variable redox conditions is largely unresolved. Peatlands provide a natural setting to study Fe–OM interactions. Utilizing chemical, spectroscopic and theoretical modeling approaches, we report the chemical forms, oxidation states and local coordination environment of naturally occurring Fe in the vertically redox-stratified Manning peatlands of western New York. In addition, we report dominant carbon, sulfur and nitrogen species that can potentially stabilize the various Fe species present in these peatlands. Our results provide clear direct and indirect evidence for the co-occurrence of ferrous (Fe2+) and ferric (Fe3+) iron species in peats under both oxic and anoxic conditions. Iron is mostly present within the operationally defined organic and amorphous (i.e., short range ordered, SRO) fractions; ferric iron primarily as magnetically isolated paramagnetic Fe3+ in Fe(III)-organic complexes, but also in mineral forms such as ferrihydrite; ferrous iron in tetrahedral coordination in Fe(II)-organic complexes with minor contribution from pyrite. All of the Fe species identified stabilize Fe(III) and/or Fe(II) in anoxic and oxic peats. Fundamental differences are also observed in the relative proportion of C, S and N functionalities of OM in oxic and anoxic peats. Aromatic CC, ester, phenol and anomeric C (ROCOR), as well as thiol, sulfide and heterocyclic N functionalities are more prevalent in anoxic peats. Collectively, our experimental evidence suggests iron forms coordination complexes with O-, S- and N-containing functional groups of OM. We posit the co-occurrence of organic and mineral forms of Fe(II) and Fe(III) in both oxic and anoxic peat layers results from dynamic complexation and hydrolysis-precipitation reactions that occur under variable redox conditions. Our findings aid in understanding the crucial role OM plays in determining Fe species in soils and sediments.

Examining the Impact of Co-branding Service Failures on Consumer Evaluations

Researchers do not fully understand consumers’ responses to negative co-branding events; thus, they report inconsistent evidence regarding the negative impact on the partnering brands. Our research bridges a gap in this research stream, and answers an important question: When a service failure occurs, could the two different models of consumers’ brand schema change affect their negative perception of each brand partner? By using a theoretical and mathematical modeling approach, we offer two propositions. The first proposition shows that, under consumers’ book-keeping cognitive process, the negative spillover effect occurs for both brands. The second proposition argues that, when the sub-typing model is assumed, it is possible that one brand suffers while the other escapes the blame for the failure. To our knowledge, this is one of the first few studies to identify circumstances in which a negative spillover effect may or may not occur to brand partners in co-branding service failures.

Modelling Orthorhombic Anisotropic Effects for Reservoir Fracture Characterization of a Naturally Fractured Tight Carbonate Reservoir, Onshore Texas, USA

In this study we present a step-by-step theoretical modelling approach, using established seismic wave propagation theories in anisotropic media, to generate unique anisotropic reflection patterns observed from three-dimensional pure-mode pressure (3D-PP), full-azimuth and full-offset seismic reflection data acquired over a naturally fractured tight carbonate field, onshore Texas, USA. Our aim is to gain an insight into the internal structures of the carbonate reservoir responsible for the observed anisotropic reflection patterns. From the generated model we were able to establish that the observed field seismic reflection patterns indicate azimuthal anisotropy in the form of crack induced shear-wave splitting and variation in P-wave velocity with offset and azimuth. Amplitude variation with azimuth (AVAZ) analysis also confirmed multi-crack sets induced anisotropy which is characteristic of orthorhombic symmetry, evident as multiple bright and dim-amplitude azimuth directions as well as complete reversal of bright-amplitude to dim-amplitude azimuth direction as the angle of incidence increases from near (≤15°) to mid (≥30°) offsets. Finally, we fitted the generated P-wave velocity into an ellipse to determine the intensity and orientation (N26E) of the open crack set as well as the direction of the minimum in situ stress axis (N116E) within the reservoir. The derived information served as an aid for the design of horizontal well paths that would intercept open fractures and ensure production optimization of the carbonate reservoir, which was on production decline despite reservoir studies that indicate un-depleted reserves.