Mechanical Engineering

Performance and economical efficiency of the combined cooling, heating and power (CCHP) system mainly depend on the system structure, operation strategy and choice of facility capacity. This paper proposes a structural configuration of the CCHP system with hybrid chillers, consisting of a combined electric and absorption chiller, whose electric cooling to cool load ratio varies according to different electric and thermal loads in every hour. A new operation strategy, based on the variational electric cooling to cool load ratio, for the CCHP system with unlimited and limited power generation unit (PGU) capacity is investigated. Given the proposed operation strategy, an optimization algorithm is adopted to determine the optimal PGU capacity. In addition, a case study of a hypothetical hotel in Victoria, BC, Canada is conducted to verify the feasibility of the proposed CCHP system structure and the corresponding optimal operation strategy.

Performance of the combined cooling, heating and power (CCHP) systems depends on the system structure, power flow strategy and the choice of facility capacity. This paper presents a matrix modeling approach to optimize the CCHP system. Modeled in a matrix form, the CCHP system can be viewed as an input–output model. Energy conversion and flow from the system input to the output is modeled by a conversion matrix including the dispatch factors and components efficiencies. By designing the objective function and determining the constraints, the optimization problem of minimizing the evaluation criteria function is solved. Furthermore, the size of the power generation unit (PGU) is also optimized to achieve the optimal performance of the CCHP system. An illustrative case study is conducted to present the effectiveness and economic efficiency of the proposed optimal power flow and operation strategy.► We model and optimize the CCHP system using a comprehensive matrix approach. ► The objective function considers energy consumption, cost and GHG emissions. ► Equality constraint for the optimization problem guarantees no energy waste. ► PGU capacity is optimized under the proposed operation strategy. ► The proposed operation strategy performs much better than FEL and FTL.

Cooperative electric vehicle (EV) charging control has emerged as a key component in grid-edge resource (GER) management. However, customers' privacy remains a major barrier to large-scale implementation of EV charging control. In this paper, we develop a distributed privacy-preserving EV charging control protocol based on secret sharing (SS) that 1) achieves scalability over EV population size; 2) enjoys higher computation efficiency compared to homomorphic encryption (HE) based methods; and 3) secures the privacy of the participating EVs against honest-but-curious adversaries and external eavesdroppers. The cooperative EV charging control is formulated to achieve overnight valley-filling and framed into the projected gradient algorithm (PGA) structure as a distributed optimization problem. SS is integrated into PGA to achieve secure updates of both primal and dual variables. Theoretical security analyses and simulations in a residential area are conducted to prove the privacy ...

Electric vehicle (EV) charging can negatively impact electric distribution networks by exceeding equipment thermal ratings and causing voltages to drop below standard ranges. In this paper, we develop a decentralized EV charging control scheme to achieve "valley-filling" (i.e., flattening demand profile during overnight charging), meanwhile meeting heterogeneous individual charging requirements and satisfying distribution network constraints. The formulated problem is an optimization problem with a non-separable objective function and strongly coupled inequality constraints. We propose a novel shrunkenprimal-dual subgradient (SPDS) algorithm to support the decentralized control scheme, derive conditions guaranteeing its convergence, and verify its efficacy and convergence with a representative distribution network model.

Large-scale multi-agent cooperative control problems have materially enjoyed the scalability, adaptivity, and flexibility of decentralized optimization. However, due to the mandatory iterative communications between the agents and the system operator, the decentralized architecture is vulnerable to malicious attacks and privacy breach. Current research on addressing privacy preservation of both agents and the system operator in cooperative decentralized optimization with strongly coupled objective functions and constraints is still primitive. To fill in the gaps, this paper proposes a novel privacy-preserving decentralized optimization paradigm based on Paillier cryptosystem. The proposed paradigm achieves ideal correctness and security, as well as resists attacks from a range of adversaries. The efficacy and efficiency of the proposed approach are verified via numerical simulations and a realworld physical platform.

Cooperatively optimizing a vast number of agents that are connected over a large-scale network brings unprecedented scalability challenges. This paper revolves around problems optimizing coupled objective functions under coupled network-induced constraints and local constraints. The scalability of existing optimization paradigms is limited by either the agent population size or the network dimension. As a radical improvement, this paper for the first time constructs a two-facet scalable decentralized optimization framework. To this end, we first develop a systemic network dimension reduction technique to virtually cluster the agents and lower the dimension of network-induced constraints, then constitute a novel shrunkenprimal-multi-dual subgradient (SPMDS) algorithm based on the reduced-dimension network. Rigorous optimality and convergence analyses of the proposed decentralized optimization framework are provided. The SPMDS-based optimization framework is free of agent-to-agent com...

Existing large-scale optimization schemes are challenged by both scalability and cyber-security. With the favorable scalability, adaptability, and flexibility, decentralized and distributed optimization paradigms are widely adopted in cyber-physical system applications. However, most existing approaches heavily rely on explicit information exchange between agents or between agents and the system operator, leading the entire framework prone to privacy risks. To tackle this issue, this paper synthesizes cryptography and decentralized optimization techniques to develop a novel privacy-preserving decentralized optimization paradigm. The proposed paradigm is generically applicable to strongly coupled convex optimization problems with nonseparable objective functions and linearly coupled constraints. The security and accuracy of the proposed paradigm are verified via numerical examples.

Recent developments in adaptive composite structures with distributed piezoelectric actuators and sensors have attracted signi®cant attention in the research community due to their potential commercial bene®ts in a wide range of applications such as vibration suppression, shape control, noise attenuation and precision positioning.

This paper investigates the mechanistic modeling of micro-milling forces, with consideration of the effects of ploughing, elastic recovery, run-out, and dynamics. A ploughing force model that takes the effect of elastic recovery into account is developed based on the interference volume between the tool and the workpiece. The elastic recovery is identified with experimental scratch tests using a conical indenter. The dynamics at the tool tip is indirectly identified by performing receptance coupling analysis through the mathematical coupling of the experimental dynamics with the analytical dynamics. The model is validated through micro end milling experiments for a wide range of cutting conditions.

The mechanical removal of materials using miniature tools, known as micro-mechanical milling processes, has unique advantages in creating miniature 3D components using a variety of engineering materials, when compared with photolithographic processes. Since the diameter of miniature tools is very small, excessive forces and vibrations significantly affect the overall quality of the part. In order to improve the part quality and longevity of tools, the monitoring of micro-milling processes is imperative. This paper examines factors affecting tool wear and a tool wear monitoring method using various sensors, such as accelerometers, force and acoustic emission sensors in micro-milling. The signals are fused through the neuro-fuzzy method, which then determines whether the tool is in good shape or is worn. An optical microscope is used to observe the actual tool condition, based upon the edge radius of the tool, during the experiment without disengaging the tool from the machine. The effectiveness of tool wear monitoring, based on a number of different sensors, is also investigated. Several cutting tests are performed to verify the monitoring scheme for the miniature micro-end mills.

This paper presents a mechanistic model for prediction of the thread milling forces. The mechanics of cutting for thread milling is analyzed similar to the end milling process but with modified cutting edge geometry. The chip thickness and cutting force models are developed considering the unique geometry of the tool. The model has been calibrated for 6061 Aluminum and validated. The effects of tool and thread geometry have been studied using the model. r

An atomization-based cutting fluid application system is developed for micro-end milling. The system was designed to ensure spreading of the droplets on the workpiece surface based on the analysis of the atomized droplet impingement dynamics. The results of the initial experiments conducted to examine the viability of the system show that the cutting forces are lower and tool life is significantly improved with the atomized cutting fluids when compared to dry and flood cooling methods. Also, application of atomized cutting fluid is found to result in good chip evacuation and lower cutting temperature. Experiments were also conducted to study the effect of fluid properties on cutting performance, and the results show that cutting fluids with lower surface tension and higher viscosity perform better in terms of cutting forces.

In this paper, a study of the effect of a transparent dielectric medium (soda-lime glass placed after an objective lens) on femtosecond pulse filamentation in Corning Eagle 2000 glass is presented. The dielectric medium placed after the objective lens increases the effective numerical aperture of the focusing lens and tightly focuses the beam to elevate the power density in a tiny focal volume. A singleshot narrow filamentary void of diameter 3.8 µm is observed to propagate as long as 700 µm in Corning Eagle 2000 glass. Elevated optical intensity confined in the small focal volume and low ionization losses per unit length in the narrow plasma column collectively enhance the filamentary propagation of the ultra-short pulse in bulk glass. The applied technique also offers an approach to control the length and width of a filamentary void structure in a transparent dielectric medium.

We demonstrate colorizing of stainless steel surfaces by femtosecond laser induced periodic microholes and micro/nano-gratings on sample surfaces. Suitable adjustment of laser induced features on stainless steel surfaces offer a variety of colors, including multi-color, gold, and black. We also report that multicolor metal surfaces exhibit diverse colors when they are exposed to the incident light of different incident and azimuthal angles. Finally, we briefly explain how the femtosecond laser induced micro/nano scale features introduce different colors on stainless steel surfaces.

A chip thickness and cutting force model that considers the deflection of the tool and the regenerative effect resulting from the presence of process faults and misalignments has been developed for the reaming process. Through a series of experiments, the model has been calibrated and validated. The model predicts tool displacement, torque, thrust, X and Y forces, and the average radius of the reamed hole. The developed model is also shown to be capable of being used as a basis for the on-line detection of process faults present in the system. r

Highly porous poly (ɛ-caprolactone) microfiber scaffolds can be fabricated using electrospinning for tissue engineering applications. Melt electrospinning produces such scaffolds by direct deposition of a polymer melt instead of dissolving the polymer in a solvent as performed during solution electrospinning. The objective of this study was to investigate the significant parameters associated with the melt electrospinning process that influence fiber diameter and scaffold morphology, including processing temperature, collection distance, applied, voltage, and nozzle size. The mechanical properties of these microfiber scaffolds varied with microfiber diameter. Additionally, the porosity of scaffolds was determined by combining experimental data with mathematical modeling. To test the cytocompatability of these fibrous scaffolds, we seeded neural progenitors derived from murine R1 embryonic stem cell lines onto these scaffolds, where they could survive, migrate, and differentiate into neurons; demonstrating the potential of these melt electrospun scaffolds for tissue engineering applications.