Mechanical Engineering

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    Davinder K. Anand - Research and Related Activities 1965-2020
    (2020-04-04) Anand, Davinder K
    Over the past fifty-five years, I have worked on problems related to dye dilution for the analysis of cardiac output, heat pipes as a high conductivity device, satellite attitude control, solar energy usage and design of systems for building heating and cooling applications, design and control of magnetically suspended flywheels for energy storage, design of magnetic bearings, magnetic spindles for high speed machining, manufacturing systems, system simulation and virtual environments as a design tool for a group of various mechanical components, and a number of unique problems of interest to me such as STEM education and R&D funding policy of the Navy.
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    EXPERIMENTAL EVALUATION AND SIMULATION RESEARCH ON NOVEL VARIABLE REFRIGERANT FLOW SYSTEM
    (2017) Lin, Xiaojie; Radermacher, Reinhard; Srebric, Jelena; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Variable refrigerant flow (VRF) system is a popular building air conditioning system which could provide cooling or heating to individual rooms independently. The system is called “variable refrigerant flow” system due to its capability of regulating the refrigerant flow via the precise control of variable speed compressors and electronic expansion valves in each indoor unit. In this dissertation, an advanced VRF system which could provide space cooling, heating and water heating is experimentally evaluated in cooling and heating season for both heat recovery operation and water heating operation. The VRF system is simulated in EnergyPlus and validated with experimental data. Based on the deviation analysis and literature review, it is found that the existing VRF model could not fully reflect the operation characteristic of VRF systems, leading to a high uncertainty in cooling/heating energy and energy consumption. A new VRF model is thereafter proposed, validated in this research and resulted in a model uncertainty less than 5%. Based on the new model, the seasonal performance of an energy saving control strategy and the concept of chilled water storage are investigated. Meanwhile, to solve the mismatch between the building’s thermal load and cooling/heating capability of the VRF system, a new VRF system with phase change material (PCM) based thermal energy storage (TES) is proposed. The new VRF system utilizes single TES device to support both cooling and heating season operation. The performance of new VRF system with PCM based TES is investigated and compared to that of the baseline VRF system. It is found that the new VRF system with PCM based TES could achieve both energy efficiency and demand response goals in cooling and heating season. Based on the comparison, the effect of operation strategies and grid incentive program are discussed. Finally, the economic analysis of the new VRF system with PCM based TES based on annual performance is carried out.
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    Simulation and Optimization of Production Control for Lean Manufacturing Transition
    (2008-08-06) Gahagan, Sean Michael; Herrmann, Jeffrey W; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Lean manufacturing is an operations management philosophy that advocates eliminating waste, including work-in-process (WIP) inventory. A common mechanism for controlling WIP is "pull" production control, which limits the amount of WIP at each stage. The process of transforming a system from push production control to pull is not well understood or studied. This dissertation explores the events of a production control transition, quantifies its costs and develops techniques to minimize them. Simulation models of systems undergoing transition from push to pull are used to study this transient behavior. The transition of a single stage system is modeled. An objective function is introduced that defines transition cost in terms of the holding cost of orders in backlog and material in inventory. It incorporates two techniques for mitigating cost: temporarily deferring orders and adding extra capacity. It is shown that, except when backlog costs are high, it is better to transform the system quickly. It is also demonstrated that simulation based optimization is a viable tool to find the optimal transition strategy. Transition of a two-stage system is also modeled. The performance of two simple multi-stage transition strategies is measured. In the first, all of the stages are transformed at the same time. In the second, they are transformed one at a time. It is shown that the latter strategy is superior. Other strategies are also discussed. A new modeling formalism, the Production Control Framework (PCF), is introduced to facilitate automated searches for transition strategies in more complex systems. It is a hierarchical description of a manufacturing system built on a novel extension of the classic queue server model, which can express production control policy parametrically. The PCF is implemented in the form of a software template and its utility is shown as it is used to model and then find the optimal production control policy for a five stage system. This work provides the first practical guidance and insight into the behavior and cost of Lean production control transition, and it lays the groundwork for the development of optimal transition strategies for even the most complex manufacturing systems.
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    Automatic Generation of Generalized Event Sequence Diagrams for Guiding Simulation Based Dynamic Probabilistic Risk Assessment of Complex Systems
    (2007-11-27) Nejad-Hosseinian, Seyed Hamed; Mosleh, Ali; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Dynamic probabilistic risk assessment (DPRA) is a systematic and comprehensive methodology that has been used and refined over the past two decades to evaluate the risks associated with complex systems such as nuclear power plants, space missions, chemical plants, and military systems. A critical step in DPRA is generating risk scenarios which are used to enumerate and assess the probability of different outcomes. The classical approach to generating risk scenarios is not, however, sufficient to deal with the complexity of the above-mentioned systems. The primary contribution of this dissertation is in offering a new method for capturing different types of engineering knowledge and using them to automatically generate risk scenarios, presented in the form of generalized event sequence diagrams, for dynamic systems. This new method, as well as several important applications, is described in detail. The most important application is within a new framework for DPRA in which the risk simulation environment is guided to explore more interesting scenarios such as low-probability/high-consequence scenarios. Another application considered is the use of the method to enhance the process of risk-based design.