Numerous Simplifications Research Articles

Składniowa „mówioność” w powieści Doroty Masłowskiej „Kochanie, zabiłam nasze koty”

Syntactic treatments, which imitate spoken language, are crucial determinants of the colloquial style, alongside lexis. Responsible for the impression of interacting or communing with the spontaneously created text, which is a record of the living language of the narrator and characters, they are concerned with numerous simplifications and schemes. Among many diversified linguistic phenomena found in the novel by D. Masłowska, entitled “Kochanie, zabiłam nasze koty” (English title: “Honey, I killed our cats”, seemingly contradictory syntactic tendencies are used; the elliptical nature of syntax on the one hand, and, on the other hand, numerous repetitions both with regards to lexis and the construction of sentences. The segmentation or breaking up of utterances, as well as their excessive expansions, is similarly contradictory. Drawing from the spoken language aims to connect the at times unreal word depicted in the novel with the reality of the recipient, and to present the literary characters in a reliable way, more often than not associated with ordinariness.

MODEL STRUCTURAL INFERENCE USING LOCAL DYNAMIC OPERATORS

This paper focuses on the problem of quantifying the effects of model-structure uncertainty in the context of time-evolving dynamical systems. This is motivated by multi-model uncertainty in computer physics simulations: developers often make different modeling choices in numerical approximations and process simplifications, leading to different numerical codes that ostensibly represent the same underlying dynamics. We consider model-structure inference as a two-step methodology: the first step is to perform system identification on numerical codes for which it is possible to observe the full state; the second step is structural uncertainty quantification (UQ), in which the goal is to search candidate models "close" to the numerical code surrogates for those that best match a quantity-of-interest (QOI) from some empirical dataset. Specifically, we: (1) define a discrete, local representation of the structure of a partial differential equation, which we refer to as the "local dynamical operator" (LDO); (2) identify model structure non-intrusively from numerical code output; (3) non-intrusively construct a reduced order model (ROM) of the numerical model through POD-DEIM-Galerkin projection; (4) perturb the ROM dynamics to approximate the behavior of alternate model structures; and (5) apply Bayesian inference and energy conservation laws to calibrate a LDO to a given QOI. We demonstrate these techniques using the two-dimensional rotating shallow water (RSW) equations as an example system.

Insight into analytical modeling of electromagnetic forming

Due to its simplicity and clear physical meaning, the analytical method is attractive for analyzing the multiphysics of electromagnetic forming; however, the reliability of the analytical method is of great concern due to numerous simplifications. Targeting on an efficient and reliable analytical model of electromagnetic forming, this paper focuses on two objectives. Firstly, we developed a multiphysics-coupled analytical model for a commonly used electromagnetic actuator—uniform pressure coil. This model considers the interaction between the electromagnetic and mechanical fields and takes the influences of the geometry and material parameters into account, thus enhancing the accuracy of the analysis. After that, we proposed a criterion to assess the applicability of a fundamental assumption made about the analytical model, that is, the magnetic field induced by the electromagnetic coil could be completely confined by the workpiece. The applicability of this assumption is of fundamental importance, as it determines the reliability of the analytical model. The proposed criterion enables the quantitative evaluation of the applicability of the assumption in terms of process parameters. We validated the proposed model by a combination of experimental, analytical, and numerical investigations. Then, we identified the effectiveness and universality of the proposed criterion by comparing it with a widely accepted one; the underlying physical foundation of the proposed criterion was also discussed. The presented study could contribute to a fundamental understanding on the analytical model of electromagnetic forming, which provides a critical guidance for an efficient and reliable analytical work.

Seismic application of multi-scale finite element model for hybrid simulation

PurposeHybrid simulation, which is a general technique for obtaining the seismic response of an entire structure, is an improvement of the traditional seismic test technique. In order to improve the analysis accuracy of the numerical substructure in hybrid simulation, the purpose of this paper is to propose an innovative hybrid simulation technique. The technique combines the multi-scale finite element (MFE) analysis method and hybrid simulation method with the objective of achieving the balance between the accuracy and efficiency for the numerical substructure simulation.Design/methodology/approachTo achieve this goal, a hybrid simulation system is established based on the MTS servo control system to develop a hybrid analysis model using an MFE model. Moreover, in order to verify the efficiency of the technique, the hybrid simulation of a three-storey benchmark structure is conducted. In this simulation, a ductile column—represented by a half-scale scale specimen—is selected as the experimental element, meanwhile the rest of the frame is modelled as microscopic and macroscopic elements in the Abaqus software simultaneously. Finally, to demonstrate the stability and accuracy of the proposed technique, the seismic response of the target structure obtained via hybrid simulation using the MFE model is compared with that of the numerical simulation.FindingsFirst, the use of the hybrid simulation with the MFE model yields results similar to those obtained by the fine finite element (FE) model using solid elements without adding excessive computing burden, thus advancing the application of the hybrid simulation in large complex structures. Moreover, the proposed hybrid simulation is found to be more versatile in structural seismic analysis than other techniques. Second, the hybrid simulation system developed in this paper can perform hybrid simulation with the MFE model as well as handle the integration and coupling of the experimental elements with the numerical substructure, which consists of the macro- and micro-level elements. Third, conducting the hybrid simulation by applying earthquake motion to simulate seismic structural behaviour is feasible by using Abaqus to model the numerical substructure and harmonise the boundary connections between three different scale elements.Research limitations/implicationsIn terms of the implementation of the hybrid simulation with the MFE model, this work is helpful to advance the hybrid simulation method in the structural experiment field. Nevertheless, there is still a need to refine and enhance the current technique, especially when the hybrid simulation is used in real complex engineering structures, having numerous micro-level elements. A large number of these elements may render the relevant hybrid simulations unattainable because the time consumed in the numeral calculations can become excessive, making the testing of the loading system almost difficult to run smoothly.Practical implicationsThe MFE model is implemented in hybrid simulation, enabling to overcome the problems related to the testing accuracy caused by the numerical substructure simplifications using only macro-level elements.Originality/valueThis paper is the first to recognise the advantage of the MFE analysis method in hybrid simulation and propose an innovative hybrid simulation technique, combining the MFE analysis method with hybrid simulation method to strike a delicate balance between the accuracy and efficiency of the numerical substructure simulation in hybrid simulation. With the help of the coordinated analysis of FEs at different scales, not only the accuracy and reliability of the overall seismic analysis of the structure is improved, but the computational cost can be restrained to ensure the efficiency of hybrid simulation.

Computing tight bounds of structural reliability under imprecise probabilistic information

In probabilistic analyses and structural reliability assessments, it is often difficult or infeasible to reliably identify the proper probabilistic models for the uncertain variables due to limited supporting databases, e.g., limited observed samples or physics-based inference. To address this difficulty, a probability-bounding approach can be utilized to model such imprecise probabilistic information, i.e., considering the bounds of the (unknown) distribution function rather than postulating a single, precisely specified distribution function. Consequently, one can only estimate the bounds of the structural reliability instead of a point estimate. Current simulation technologies, however, sacrifice precision of the bound estimate in return for numerical efficiency through numerical simplifications. Hence, they produce overly conservative results in many practical cases. This paper proposes a linear programming-based method to perform reliability assessments subjected to imprecisely known random variables. The method computes the tight bounds of structural failure probability directly without the need of constructing the probability bounds of the input random variables. The method can further be used to construct the best-possible bounds for the distribution function of a random variable with incomplete statistical information.

Partially-static data as free extension of algebras

Partially-static data structures are a well-known technique for improving binding times. However, they are often defined in an ad-hoc manner, without a unifying framework to ensure full use of the equations associated with each operation. We present a foundational view of partially-static data structures as free extensions of algebras for suitable equational theories, i.e. the coproduct of an algebra and a free algebra in the category of algebras and their homomorphisms. By precalculating these free extensions, we construct a high-level library of partially-static data representations for common algebraic structures. We demonstrate our library with common use-cases from the literature: string and list manipulation, linear algebra, and numerical simplification.

Exact results for the Floquet coin toss for driven integrable models

We study an integrable Hamiltonian reducible to free fermions which is subjected to an imperfect periodic driving with the amplitude of driving (or kicking) randomly chosen from a binary distribution like a coin-toss problem. The randomness present in the driving protocol destabilises the periodic steady state, reached in the limit of perfectly periodic driving, leading to a monotonic rise of the stroboscopic residual energy with the number of periods ($N$). We establish that a minimal deviation from the perfectly periodic driving would always result in a {\it bounded} heating up of the system with $N$ to an asymptotic finite value. Remarkably, exploiting the completely uncorrelated nature of the randomness and the knowledge of the stroboscopic Floquet operator in the perfectly periodic situation, we provide an exact analytical formalism to derive the disorder averaged expectation value of the residual energy through a {\it disorder operator}. This formalism not only leads to an immense numerical simplification, but also enables us to derive an exact analytical form for the residual energy in the asymptotic limit which is universal, i.e, independent of the bias of coin-toss and the protocol chosen. Furthermore, this formalism clearly establishes the nature of the monotonic growth of the residual energy at intermediate $N$ while clearly revealing the possible non-universal behaviour of the same.

Correction of Model Reduction Errors in Simulations

In simulations of complex physical phenomena, model reductions are often required to decrease the computation time of the simulation model to a feasible level. Model reduction is often obtained by using a reduced model, which may be based on a reduced numerical approximation and simplifications of the underlying accurate model. The use of a reduced model, however, induces errors to the simulation results. In this paper, we describe and evaluate a novel approach for the correction of the approximation errors in reduced simulation models. The key idea is to model the approximation error between the accurate and reduced simulation model as an additive noise term to the reduced model and construct a low-cost predictor model for the approximation error based on statistical learning. In this paper, the approximation error approach is evaluated with the following problems: correction of spatial and temporal discretization errors in a time-varying heat equation--based evolution model, correction of spatial discre...

Analytic Model for Tangential YORP

Abstract The tangential YORP effect (TYORP) plays a significant role in the dynamical evolution of asteroids, and up to now has only been studied numerically. This paper describes the first analytic model of the TYORP effect. Although the model rests on numerous physical and mathematical simplifications, the final analytic expression for TYORP is found to be in agreement with the results of rigorous numeric simulations to the accuracy of several tens of percent. The analytic expression obtained is used to estimate the TYORP produced by the non-flat surface of regolith—a contribution to TYORP that has never been considered. It is found that the contribution to TYORP arising from regolith can be comparable to the conventional TYORP produced by boulders. Then, the analytic expression is fitted with a log-normal function and used to integrate TYORP over all boulder sizes. The general trend of TYORP for multiple boulders appears qualitatively similar to the trend of one boulder, and it also demonstrates a maximal TYORP at some particular rotation rate. The expression obtained for integrated TYORP may be instrumental for simulations of the evolution of asteroids subject to TYORP. The physical origin of TYORP is discussed in light of the constructed analytic model.

CONTRA-ROTATING PROPELLER AERODYNAMICS SOLVED BY A 3D PANEL METHOD WITH COUPLED BOUNDARY LAYER

The aerodynamics of contra-rotating propellers is a complex three-dimensional problem of an unsteady flow, which is often approached by assuming numerous simplifications. Presented computational model combines a 3D panel method with a force-free vortex wake and a two-dimensional two-equation boundary layer model in an attempt to capture all the main contributing elements of the flow physics. An emphasis is placed on the interaction of the viscous boundary layer region with the inviscid region and the development of a portable method of their coupling. The kinematics of a force-free vortex wake is supplemented with a vortex aging due to a diffusion. Extra attention is paid to the process of the blade passing through the wake of another blade. To demonstrate the ability of the numerical model, several test cases are presented, illustrating the reaction of the system to various operational conditions.

Numerical Limitations of 1D Hydraulic Models Using MIKE11 or HEC-RAS software – Case study of Baraolt River, Romania

MIKE 11 is an advanced hydroinformatic tool, a professional engineering software package for simulation of one-dimensional flows in estuaries, rivers, irrigation systems, channels and other water bodies. MIKE 11 is a 1-dimensional river model. It was developed by DHI Water · Environment · Health, Denmark. The basic computational procedure of HEC-RAS for steady flow is based on the solution of the one-dimensional energy equation. Energy losses are evaluated by friction and contraction / expansion. The momentum equation may be used in situations where the water surface profile is rapidly varied. These situations include hydraulic jumps, hydraulics of bridges, and evaluating profiles at river confluences. For unsteady flow, HEC-RAS solves the full, dynamic, 1-D Saint Venant Equation using an implicit, finite difference method. The unsteady flow equation solver was adapted from Dr. Robert L. Barkau’s UNET package. Fluid motion is controlled by the basic principles of conservation of mass, energy and momentum, which form the basis of fluid mechanics and hydraulic engineering. Complex flow situations must be solved using empirical approximations and numerical models, which are based on derivations of the basic principles (backwater equation, Navier-Stokes equation etc.). All numerical models are required to make some form of approximation to solve these principles, and consequently all have their limitations. The study of hydraulics and fluid mechanics is founded on the three basic principles of conservation of mass, energy and momentum. Real-life situations are frequently too complex to solve without the aid of numerical models. There is a tendency among some engineers to discard the basic principles taught at university and blindly assume that the results produced by the model are correct. Regardless of the complexity of models and despite the claims of their developers, all numerical models are required to make approximations. These may be related to geometric limitations, numerical simplification, or the use of empirical correlations. Some are obvious: one-dimensional models must average properties over the two remaining directions. It is the less obvious and poorly advertised approximations that pose the greatest threat to the novice user. Some of these, such as the inability of one-dimensional unsteady models to simulate supercritical flow can cause significant inaccuracy in the model predictions.

On non-local energy transfer via zonal flow in the Dimits shift

The two-dimensional Terry–Horton equation is shown to exhibit the Dimits shift when suitably modified to capture both the nonlinear enhancement of zonal/drift-wave interactions and the existence of residual Rosenbluth–Hinton states. This phenomenon persists through numerous simplifications of the equation, including a quasilinear approximation as well as a four-mode truncation. It is shown that the use of an appropriate adiabatic electron response, for which the electrons are not affected by the flux-averaged potential, results in an $\boldsymbol{E}\times \boldsymbol{B}$ nonlinearity that can efficiently transfer energy non-locally to length scales of the order of the sound radius. The size of the shift for the nonlinear system is heuristically calculated and found to be in excellent agreement with numerical solutions. The existence of the Dimits shift for this system is then understood as an ability of the unstable primary modes to efficiently couple to stable modes at smaller scales, and the shift ends when these stable modes eventually destabilize as the density gradient is increased. This non-local mechanism of energy transfer is argued to be generically important even for more physically complete systems.

High-Pressure Modeling of Asphaltene Precipitation during Oil Depletion Based on the Solid Model

Asphaltene precipitation is a complex and serious problem in all sectors of the oil industry because it has a severe and detrimental impact on oil production. Thus, it is crucial to investigate under which conditions asphaltenes precipitate in order to prevent or mitigate the effects. Several approaches have been reported in the literature regarding the modeling of asphaltene precipitation during oil production. The simplest one is the single-component solid model in which the precipitated asphaltene is considered a pure solid and the oil and gas phases are described by a cubic equation of state (EOS). These are the basic assumptions of the Nghiem and Coombe’s model. In this paper, based on this model, we make numerous improvements and simplifications such as reducing the number of parameters to be estimated and considering that the number of asphaltene fractions can vary according to the oil characteristics. The characterization method is performed using the exponential distribution and only the binary i...

Koncepcja walidacji efektów uczenia się: obszary pedagogicznych redukcji i ich (nie)zamierzonych skutków

The paper is an attempt to problematize the concept of the validation of learning outcomes, which is a component of the process of recognition of qualifications. Viewing itfrom the perspective of the policy of simplicity (Krajewski 2013) makes it possible to trace areas, generated by its subject matter and practical applications, of utilitarian reductions of complex educational and social reality. The recognition of the character of these reductions and their potential consequences have been subjected to the sequential logic of analytic categories derived from the unitary theory of validity by Samuel Messick (1989). The analyses conducted unravel superficial atheoreticalness and neutrality of validation and the role which in the process of its implementation and popularisation is played by creation of a “new” language, essentially tainted with liberal newspeak (Bihr 2008). The reflections undertaken confirm that effects possible to observe and anticipate of numerous simplifications, exclusions and concealments have generated a procedurally complex and unclear picture of social knowledge and educational action, in which only a group of narrowly specialised experts efficiently move. The conclusion contains the thesis that the fact of the concept of the validation of learning outcomes being appropriated by one discourse ideologically subservient to the neoliberal concept of education creates conditions favouring construction of a world of pretences and axiological relativism, which can be prevented by multi-faceted and critical reflection on it, open to reality.

Bio-Inspired Heuristic Network Configuration in Air Transportation System-of-Systems Design Optimization

Previous work in air transportation system-of-systems (ATSoSs) design optimization considered integrated aircraft sizing, fleet allocation, and route network configuration. The associated nested multidisciplinary formulation posed a numerically challenging blackbox optimization problem; therefore, direct search methods with convergence properties were used to solve it. However, the complexity of the blackbox impedes greatly the solution of larger-scale problems, where the number of considered nodes in the route network is high. The research presented here adopts a rule-based route network design inspired by biological transfer principles. This bio-inspired approach decouples the network configuration problem from the optimization loop, leading to significant numerical simplifications. The usefulness of the bio-inspired approach is demonstrated by comparing its results to those obtained using the nested formulation for a 15 city network. We then consider introduction of new aircraft as well as a larger problem with 20 cities.

Nvestment Appraisal in the Public Sector – Incorporating Flexibility and Environmental Impact

The public sector often invests in large projects in different sectors, such as education, health care and infrastructure. It can be argued that investment appraisal process in these projects should differ from conventional approaches due to the complex interests the public sector holds, which often implies that several aspects need to be considered. Conventional techniques may not suffice and therefore this thesis aims to investigate the applicability of real options analysis and multi-criteria analysis in a combined approach. The study is conducted in the form of a case study at publicly owned Sundsvalls Logistikpark, where options in the form of the utilization of development areas and the non-monetary aspect reduction of carbon dioxide are included in the appraisal. The model developed compares two alternative strategies where one is based upon conventional usage of the area and the other represents the environmentally friendly alternative. The results show that including the value of flexibility in the appraisal significantly raises the initial valuation, whereas the comparison of the strategies show that the results either details which strategy is preferred, if input to both strategies are available, or where the threshold for indifference lies. It is concluded that this model is applicable in terms of its ability to capture the value of flexibility and inclusion of several aspects of the decision problem. However, it is also concluded that the numerous simplifications made may lead to unreliability in the results, and the process of obtaining accurate input may time-consuming, depending on the case. The usability of the model is high in terms of its potential, but lower in terms of the knowledge-based threshold required of the user.

Certainly uncertain - the charm of fuzzy predictions

A common problem in the numerical simulation of complex real-world systems is the fact that the parameters of the models usually exhibit some degree of uncertainty and exact values for their quantification can hardly be provided. This non-determinism in numerical models may arise as a consequence of different sources: on the one hand, natural variability or scatter, on the other hand, uncertainties that arise from an absence of information, vagueness in parameter definition, subjectivity in numerical implementation, or simplification and idealization as it usually appears in every modeling procedure. As one possible approach to solve this limitation, an interdisciplinary methodology to an advanced modeling and analysis of systems is presented, which allows for the inclusion of uncertainties from the very beginning of the modeling procedure. This approach is based on fuzzy arithmetic, a special field of fuzzy set theory, where the uncertain values of the model parameters are represented by so-called fuzzy numbers, reflecting in a rather intuitive and plausible way the blurred range of possible parameter values. As a result of this special modeling technique, more comprehensive system models can be derived which outperform the conventional, crisp-parameterized models by providing simulation results which reflect both the system dynamics and the effect of the uncertainties. The methodology is exemplarily illustrated by an application from the field of automotive crash simulation which demonstrates that advanced modeling and simulation of dynamical systems, based on fuzzy arithmetical techniques for including the presumably limiting uncertainties, can provide significant additional benefit. A variety of further applications from other fields of the engineering sciences is given in the references, highlighting the charm of fuzzy predictions.

Knowledge gaps in host-parasite interaction preclude accurate assessment of meat-borne exposure to Toxoplasma gondii

Toxoplasma gondii is recognized as a widely prevalent zoonotic parasite worldwide. Although several studies clearly identified meat products as an important source of T. gondii infections in humans, quantitative understanding of the risk posed to humans through the food chain is surprisingly scant. While probabilistic risk assessments for pathogens such as Campylobacter jejuni, Listeria monocytogenes or Escherichia coli have been well established, attempts to quantify the probability of human exposure to T. gondii through consumption of food products of animal origin are at early stages. The biological complexity of the life cycle of T. gondii and limited understanding of several fundamental aspects of the host/parasite interaction, require the adoption of numerous critical assumptions and significant simplifications. In this study, we present a hypothetical quantitative model for the assessment of human exposure to T. gondii through meat products. The model has been conceptualized to capture the dynamics leading to the presence of parasite in meat and, for illustrative purposes, used to estimate the probability of at least one viable cyst occurring in 100g of fresh pork meat in England. Available data, including the results of a serological survey in pigs raised in England were used as a starting point to implement a probabilistic model and assess the fate of the parasite along the food chain. Uncertainty distributions were included to describe and account for the lack of knowledge where necessary. To quantify the impact of the key model inputs, sensitivity and scenario analyses were performed. The overall probability of 100g of a hypothetical edible tissue containing at least 1 cyst was 5.54%. Sensitivity analysis indicated that the variables exerting the greater effect on the output mean were the number of cysts and number of bradyzoites per cyst. Under the best and the worst scenarios, the probability of a single portion of fresh pork meat containing at least 1 viable cyst resulted 1.14% and 9.97% indicating that the uncertainty and lack of data surrounding key input parameters of the model preclude accurate estimation of T. gondii exposure through consumption of meat products. The hypothetical model conceptualized here is coherent with current knowledge of the biology of the parasite. Simulation outputs clearly identify the key gaps in our knowledge of the host-parasite interaction that, when filled, will support quantitative assessments and much needed accurate estimates of the risk of human exposure.

Sensitivity Analysis of a Riparian Vegetation Growth Model

The paper presents a sensitivity analysis of two main parameters used in a mathematic model able to evaluate the effects of changing hydrology on the growth of riparian vegetation along rivers and its effects on the cross-section width. Due to a lack of data in existing literature, in a past study the schematization proposed here was applied only to two large rivers, assuming steady conditions for the vegetational carrying capacity and coupling the vegetal model with a 1D description of the river morphology. In this paper, the limitation set by steady conditions is overcome, imposing the vegetational evolution dependent upon the initial plant population and the growth rate, which represents the potential growth of the overall vegetation along the watercourse. The sensitivity analysis shows that, regardless of the initial population density, the growth rate can be considered the main parameter defining the development of riparian vegetation, but it results site-specific effects, with significant differences for large and small rivers. Despite the numerous simplifications adopted and the small database analyzed, the comparison between measured and computed river widths shows a quite good capability of the model in representing the typical interactions between riparian vegetation and water flow occurring along watercourses. After a thorough calibration, the relatively simple structure of the code permits further developments and applications to a wide range of alluvial rivers.

Bringing hemodynamic simulations closer to the clinics: a CFD prototype study for intracranial aneurysms.

Computational Fluid Dynamics enables the investigation of patient-specific hemodynamics for rupture predictions and treatment support of intracranial aneurysms. However, due to numerous simplifications to decrease the computations effort, clinical applicability is limited until now. To overcome this situation a clinical research software prototype was tested that can be easily operated by attending physicians. In order to evaluate the accuracy of this prototype, four patient-specific intracranial aneurysms were investigated using four different spatial resolutions. The results demonstrate that physicians were able to generate hemodynamic predictions within several minutes at low spatial resolution. However, depending on the parameter of interest and the desired accuracy, higher resolutions are required, which will lead to an increase of computational times that still look very attractive towards clinical usability. The study shows that the next step towards an applicable individualized therapy for patients harboring intracranial aneurysms can be done. However, further in vivo validations are required to guarantee realistic predictions in future studies.