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Grado Department of Industrial and Systems Engineering

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https://hdl.handle.net/10919/24217

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Browsing Grado Department of Industrial and Systems Engineering by Department "Civil and Environmental Engineering"

Now showing 1 - 4 of 4
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    Occupational Safety and Health Concerns in Logging: A Cross-Sectional Assessment in Virginia
    Kim, Sunwook; Nussbaum, Maury A.; Schoenfisch, Ashley L.; Barrett, Scott M.; Bolding, M. Chad; Dickerson, Deborah E. (MDPI, 2017-11-15)
    Increased logging mechanization has helped improve logging safety and health, yet related safety risks and concerns are not well understood. A cross-sectional study was completed among Virginia loggers. Participants n = 122) completed a self-administered questionnaire focusing on aspects of safety and health related to logging equipment. Respondents were at a high risk of workplace injuries, with reported career and 12-month injury prevalences of 51% and 14%, respectively. Further, nearly all (98%) respondents reported experiencing musculoskeletal symptoms. Over half (57.4%) of respondents reported symptoms related to diesel exhaust exposure in their career. Few (15.6%), however, perceived their jobs to be dangerous. Based on the opinions and suggestions of respondents, three priority areas were identified for interventions: struck-by/against hazards, situational awareness (SA) during logging operations, and visibility hazards. To address these hazards, and to have a broader and more substantial positive impact on safety and health, we discuss the need for proactive approaches such as incorporating proximity technologies in a logging machine or personal equipment, and enhancing logging machine design to enhance safety, ergonomics, and SA.
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    An Optimal Constrained Pruning Strategy for Decision Trees
    Sherali, Hanif D.; Hobeika, Antoine G.; Jeenanunta, Chawalit (INFORMS, 2009)
    This paper is concerned with the optimal constrained pruning of decision trees. We present a novel 0-1 programming model for pruning the tree to minimize some general penalty function based on the resulting leaf nodes, and show that this model possesses a totally unimodular structure that enables it to be solved as a shortest-path problem on an acyclic graph. Moreover, we prove that this problem can be solved in strongly polynomial time while incorporating an additional constraint on the number of residual leaf nodes. Furthermore, the framework of the proposed modeling approach renders it suitable to accommodate different (multiple) objective functions and side-constraints, and we identify various such modeling options that can be applied in practice. The developed methodology is illustrated using a numerical example to provide insights, and some computational results are presented to demonstrate the efficacy of solving generically constrained problems of this type. We also apply this technique to a large-scale transportation analysis and simulation system (TRANSIMS), and present related computational results using real data to exhibit the flexibility and effectiveness of the proposed approach.
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    A Review of Modeling Bioelectrochemical Systems: Engineering and Statistical Aspects
    Luo, Shuai; Sun, Hongyue; Ping, Qingyun; Jin, Ran; He, Zhen (MDPI, 2016-02-18)
    Bioelectrochemical systems (BES) are promising technologies to convert organic compounds in wastewater to electrical energy through a series of complex physical-chemical, biological and electrochemical processes. Representative BES such as microbial fuel cells (MFCs) have been studied and advanced for energy recovery. Substantial experimental and modeling efforts have been made for investigating the processes involved in electricity generation toward the improvement of the BES performance for practical applications. However, there are many parameters that will potentially affect these processes, thereby making the optimization of system performance hard to be achieved. Mathematical models, including engineering models and statistical models, are powerful tools to help understand the interactions among the parameters in BES and perform optimization of BES configuration/operation. This review paper aims to introduce and discuss the recent developments of BES modeling from engineering and statistical aspects, including analysis on the model structure, description of application cases and sensitivity analysis of various parameters. It is expected to serves as a compass for integrating the engineering and statistical modeling strategies to improve model accuracy for BES development.
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    Socio-technical scales in socio-environmental modeling: Managing a system-of-systems modeling approach
    Iwanaga, Takuya; Wang, Hsiao-Hsuan; Hamilton, Serena H.; Grimm, Volker; Koralewski, Tomasz E.; Salado, Alejandro; Elsawah, Sondoss; Razavi, Saman; Yang, Jing; Glynn, Pierre; Badham, Jennifer; Voinov, Alexey; Chen, Min; Grant, William E.; Peterson, Tarla Rai; Frank, Karin; Shenk, Gary; Barton, C. Michael; Jakeman, Anthony J.; Little, John C. (2021-01)
    System-of-systems approaches for integrated assessments have become prevalent in recent years. Such approaches integrate a variety of models from different disciplines and modeling paradigms to represent a socioenvironmental (or social-ecological) system aiming to holistically inform policy and decision-making processes. Central to the system-of-systems approaches is the representation of systems in a multi-tier framework with nested scales. Current modeling paradigms, however, have disciplinary-specific lineage, leading to inconsistencies in the conceptualization and integration of socio-environmental systems. In this paper, a multidisciplinary team of researchers, from engineering, natural and social sciences, have come together to detail socio-technical practices and challenges that arise in the consideration of scale throughout the socioenvironmental modeling process. We identify key paths forward, focused on explicit consideration of scale and uncertainty, strengthening interdisciplinary communication, and improvement of the documentation process. We call for a grand vision (and commensurate funding) for holistic system-of-systems research that engages researchers, stakeholders, and policy makers in a multi-tiered process for the co-creation of knowledge and solutions to major socio-environmental problems.