scholarly journals An automated methodology to select functional co-simulation configurations

2019 ◽  
Vol 48 (1) ◽  
pp. 79-103 ◽  
Author(s):  
Jarkko Rahikainen ◽  
Francisco González ◽  
Miguel Ángel Naya

Abstract The development of machinery often requires system-level analysis, in which non-mechanical subsystems, such as hydraulics, need to be considered. Co-simulation allows analysts to divide a problem into subsystems and use tailored software solutions to deal individually with their respective dynamics. On the other hand, these subsystems must be coupled at particular instants in time, called communication points, through the exchange of coupling variables. Between communication points, each subsystem solver carries out the integration of its states without interacting with its environment. This may cause the integration to become unstable, especially when non-iterative co-simulation is used. The co-simulation configuration, i.e., the parameters and simulation options selected by the analyst, such as the way to handle the coupling variables or the choice of subsystem solvers, is often a critical factor regarding co-simulation stability. In practice it is difficult to anticipate which selection is the most appropriate for a particular problem, especially if some inputs come from external sources, such as human operators, and cannot be determined beforehand. We put forward a methodology to automatically determine a stable and computationally efficient configuration for Jacobi-scheme co-simulation. The method uses energy residuals to gain insight into co-simulation stability. The relation between energy residual and communication step-size is exploited to monitor co-simulation accuracy during a series of tests in which the external inputs are replaced with predetermined input functions. The method was tested with hydraulically actuated mechanical examples. Results indicate that the proposed method can be used to find stable and accurate configurations for co-simulation applications.

Author(s):  
Weitao Chen ◽  
Shenhai Ran ◽  
Canhui Wu ◽  
Bengt Jacobson

AbstractCo-simulation is widely used in the industry for the simulation of multidomain systems. Because the coupling variables cannot be communicated continuously, the co-simulation results can be unstable and inaccurate, especially when an explicit parallel approach is applied. To address this issue, new coupling methods to improve the stability and accuracy have been developed in recent years. However, the assessment of their performance is sometimes not straightforward or is even impossible owing to the case-dependent effect. The selection of the coupling method and its tuning cannot be performed before running the co-simulation, especially with a time-varying system.In this work, the co-simulation system is analyzed in the frequency domain as a sampled-data interconnection. Then a new coupling method based on the H-infinity synthesis is developed. The method intends to reconstruct the coupling variable by adding a compensator and smoother at the interface and to minimize the error from the sample-hold process. A convergence analysis in the frequency domain shows that the coupling error can be reduced in a wide frequency range, which implies good robustness. The new method is verified using two co-simulation cases. The first case is a dual mass–spring–damper system with random parameters and the second case is a co-simulation of a multibody dynamic (MBD) vehicle model and an electric power-assisted steering (EPAS) system model. Experimental results show that the method can improve the stability and accuracy, which enables a larger communication step to speed up the explicit parallel co-simulation.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Nisha Bhardwaj ◽  
Bikash Kumar ◽  
Komal Agrawal ◽  
Pradeep Verma

AbstractThe potential of cellulolytic enzymes has been widely studied and explored for bioconversion processes and plays a key role in various industrial applications. Cellulase, a key enzyme for cellulose-rich waste feedstock-based biorefinery, has increasing demand in various industries, e.g., paper and pulp, juice clarification, etc. Also, there has been constant progress in developing new strategies to enhance its production, such as the application of waste feedstock as the substrate for the production of individual or enzyme cocktails, process parameters control, and genetic manipulations for enzyme production with enhanced yield, efficiency, and specificity. Further, an insight into immobilization techniques has also been presented for improved reusability of cellulase, a critical factor that controls the cost of the enzyme at an industrial scale. In addition, the review also gives an insight into the status of the significant application of cellulase in the industrial sector, with its techno-economic analysis for future applications. The present review gives a complete overview of current perspectives on the production of microbial cellulases as a promising tool to develop a sustainable and greener concept for industrial applications.


Author(s):  
Zhijin Song ◽  
Huizi Wang ◽  
Jian Sun ◽  
Ye Tian

Micro-simulation packages provide an efficient and systematic approach to depicting traffic dynamics. Nonetheless, many of these models used by the micro-simulation packages are only calibrated with respect to observed traffic indicators such as average speed, traffic count, and so forth, while omitting non-traffic indicators. This paper aims to investigate the performance of VISSIM and TransModeler when depicting non-traffic indicators such as fuel consumption, emissions, and safety. A model was first calibrated for traffic indicators based on Next Generation SIMulation (NGSIM) trajectories. Results indicated that after calibration, simulation accuracy was still unsatisfactory with regard to energy consumption and emission measurements, with errors of up to 38.23% in VISSIM. In assessing safety, the relative error of VISSIM increased from 12.36% to 59.92% after calibration. The error in TransModeler increased to almost 100%. Furthermore, this study explored the simulation accuracy of VISSIM and TransModeler under different traffic conditions and discovered that the models’ accuracies were relatively high when simulating stop-and-go traffic. We also explored the causes of these observed differences through a regression model. This study presents practical insight into the deficiencies of micro-simulation related research, and based on error analysis, provides a theoretical reference for optimizing simulation accuracy from a novel perspective.


2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Zhanwei Xuan ◽  
Xiang Feng ◽  
Jingwen Yu ◽  
Pengyao Ping ◽  
Haochen Zhao ◽  
...  

A lot of research studies have shown that many complex human diseases are associated not only with microRNAs (miRNAs) but also with long noncoding RNAs (lncRNAs). However, most of the current existing studies focus on the prediction of disease-related miRNAs or lncRNAs, and to our knowledge, until now, there are few literature studies reported to pay attention to the study of impact of miRNA-lncRNA pairs on diseases, although more and more studies have shown that both lncRNAs and miRNAs play important roles in cell proliferation and differentiation during the recent years. The identification of disease-related genes provides great insight into the underlying pathogenesis of diseases at a system level. In this study, a novel model called PADLMHOOI was proposed to predict potential associations between diseases and lncRNA-miRNA pairs based on the higher-order orthogonal iteration, and in order to evaluate its prediction performance, the global and local LOOCV were implemented, respectively, and simulation results demonstrated that PADLMHOOI could achieve reliable AUCs of 0.9545 and 0.8874 in global and local LOOCV separately. Moreover, case studies further demonstrated the effectiveness of PADLMHOOI to infer unknown disease-related lncRNA-miRNA pairs.


2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Sigrun Hvalvik ◽  
Bjørg Dale

Older persons in transition to need professional care in their homes will constitute a large group in municipalities in the future. The aim of this study was to obtain insight into nurses' experiences and perceptions of caring for patients in transition to receive homecare. Eleven home nurses divided into two focus groups were interviewed, and a phenomenological hermeneutical design was used. Four interpretations closely related to each other were revealed: it is essential to have an understanding of the patients' transition history; the nurse' repertoire is challenged in the transition process; care must be adapted to the patients' life world; the excellence of care is threatened by the context. The nurses strived to provide care based upon respect for the independent individual as a living whole. Their ambitions were, however, challenged and threatened by the caring context. The cooperation across organizational levels was pointed out as a critical factor with potential for improvement. This must be taken seriously to support the nurses in their endeavors to provide excellent care.


2019 ◽  
Vol 86 (8) ◽  
Author(s):  
Weicheng Huang ◽  
Mohammad Khalid Jawed

Discrete elastic rods (DER) algorithm presents a computationally efficient means of simulating the geometrically nonlinear dynamics of elastic rods. However, it can suffer from artificial energy loss during the time integration step. Our approach extends the existing DER technique by using a different time integration scheme—we consider a second-order, implicit Newmark-beta method to avoid energy dissipation. This treatment shows better convergence with time step size, specially when the damping forces are negligible and the structure undergoes vibratory motion. Two demonstrations—a cantilever beam and a helical rod hanging under gravity—are used to show the effectiveness of the modified discrete elastic rods simulator.


2014 ◽  
Vol 29 (2) ◽  
pp. 125-145 ◽  
Author(s):  
Evan H. Offstein ◽  
Raymond Kniphuisen ◽  
D. Robin Bichy ◽  
J. Stephen Childers Jr

Purpose – Recent lapses in the management of high hazard organizations, such as the Fukushima event or the Deepwater Horizon blast, add considerable urgency to better understand the complicated and complex phenomena of leading and managing high reliability organizations (HRO). The purpose of this paper is to offer both theoretical and practical insight to further strengthen reliability in high hazard organizations. Design/methodology/approach – Phenomenological study based on over three years of research and thousands of hours of study in HROs conducted through a scholar-practitioner partnership. Findings – The findings indicate that the identification and the management of competing tensions arising from misalignment within and between public policy, organizational strategy, communication, decision-making, organizational learning, and leadership is the critical factor in explaining improved reliability and safety of HROs. Research limitations/implications – Stops short of full-blown grounded theory. Steps were made to ensure validity; however, generalizability may be limited due to sample. Practical implications – Provides insight into reliably operating organizations that are crucial to society where errors would cause significant damage or loss. Originality/value – Extends high reliability research by investigating more fully the competing tensions present in these complex, societally crucial organizations.


2008 ◽  
Vol 2008 ◽  
pp. 1-38 ◽  
Author(s):  
Firdaus E. Udwadia ◽  
Artin Farahani

Standard Runge-Kutta methods are explicit, one-step, and generally constant step-size numerical integrators for the solution of initial value problems. Such integration schemes of orders 3, 4, and 5 require 3, 4, and 6 function evaluations per time step of integration, respectively. In this paper, we propose a set of simple, explicit, and constant step-size Accerelated-Runge-Kutta methods that are two-step in nature. For orders 3, 4, and 5, they require only 2, 3, and 5 function evaluations per time step, respectively. Therefore, they are more computationally efficient at achieving the same order of local accuracy. We present here the derivation and optimization of these accelerated integration methods. We include the proof of convergence and stability under certain conditions as well as stability regions for finite step sizes. Several numerical examples are provided to illustrate the accuracy, stability, and efficiency of the proposed methods in comparison with standard Runge-Kutta methods.


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