Effects of Metal Absorber Thermal Conductivity on Clear Plastic Laser Transmission Welding

In our previous study, metals have been used as absorbers in the clear plastic laser transmission welding. The effects of metal thermal conductivity on the welding quality are investigated in the present work. Four metals with distinctly different thermal conductivities, i.e., titanium, nickel, molybdenum, and copper, are selected as light absorbers. The lap welding is conducted with an 808 nm diode laser and simulation experiments are also conducted. Nickel electroplating test is carried out to minimize the side-effects from different light absorptivities of different metals. The results show that the welding with an absorber of higher thermal conductivity can accommodate higher laser input power before smoking, which produces a wider and stronger welding seam.The positive role of the higher thermal conductivity can be attributed to the fact that a desirable thermal field distribution for the molecular diffusion and entanglement is produced from the case with a high thermal conductivity.

Design for a Novel Framework of Hyper-Heuristic Algorithm

A novel framework of hyper-heuristic algorithm was proposed to improve the adaption of evolutionary algorithms( EAs)in optimization. The algorithm could be changed during the evolutionary progress according to their performances. In addition,a large number of elite individuals were employed in the algorithm and the elite individuals helped algorithm achieve a better performance,while such number of elite individuals stagnated the global convergence in conventional single algorithm. The time complexity was analyzed to demonstrate the novel framework did not increase the time complexity. The simulation results indicate that the proposed framework outperforms any single algorithm that composes the framework.

Cooperative Optimization of Reconfigurable Machine Tool Configurations and Production Process Plan

The production process plan design and configurations of reconfigurable machine tool （RMT） interact with each other. Reasonable process plans with suitable configurations of RMT help to improve product quality and reduce production cost. Therefore, a cooperative strategy is needed to concurrently solve the above issue. In this paper, the cooperative optimization model for RMT configurations and production process plan is presented. Its objectives take into account both impacts of process and configuration. Moreover, a novel genetic algorithm is also developed to provide optimal or near-optimal solutions： firstly, its chromosome is redesigned which is composed of three parts, operations, process plan and configurations of RMTs, respectively; secondly, its new selection, crossover and mutation operators are also developed to deal with the process constraints from operation processes （OP） graph, otherwise these operators could generate illegal solutions violating the limits; eventually the optimal configurations for RMT under optimal process plan design can be obtained. At last, a manufacturing line case is applied which is composed of three RMTs. It is shown from the case that the optimal process plan and configurations of RMT are concurrently obtained, and the production cost decreases 6.28% and nonmonetary performance increases 22%. The proposed method can figure out both RMT configurations and production process, improve production capacity, functions and equipment utilization for RMT.

Solution-Distance-Based Migration Rate Calculating for Biogeography-Based Optimization

Biogeography-based optimization(BBO),a natureinspired optimization algorithm(NIOA),has exhibited a huge potential in optimization.In BBO,the good solutions have a large probability to share information with poor solutions,while poor solutions have a large probability to accept the information from others.In original BBO,calculating for migration rates is based on solutions' ranking.From the ranking,it can be known that which solution is better and which one is worse.Based on the ranking,the migration rates are calculated to help BBO select good features and poor features.The differences among results can not be reflected,which will result in an improper migration rate calculating.Two new ways are proposed to calculate migration rates,which is helpful for BBO to obtain a suitable assignment of migration rates and furthermore affect algorithms ' performance.The ranking of solutions is no longer integers,but decimals.By employing the strategies,the ranking can not only reflect the orders of solutions,but also can reflect more details about solutions' distances.A set of benchmarks,which include 14 functions,is employed to compare the proposed approaches with other algorithms.The results demonstrate that the proposed approaches are feasible and effective to enhance BBO's performance.

Building dynamic thermal simulation of low-order multi-dimensional heat transfer

Multi-dimensional heat transfers modeling is crucial for building simulations of insulated buildings,which are widely used and have multi-dimensional heat transfers characteristics.For this work,state-model-reduction techniques were used to develop a reduced low-order model of multi-dimensional heat transfers.With hot box experiment of hollow block wall,heat flow relative errors between experiment and low-order model predication were less than 8% and the largest errors were less than 3%.Also,frequency responses of five typical walls,each with different thermal masses or insulation modes,the low-order model and the complete model showed that the low-order model results agree very well in the lower excitation frequency band with deviations appearing only at high frequency.Furthermore,low-order model was used on intersection thermal bridge of a floor slab and exterior wall.Results show that errors between the two models are very small.This low-order model could be coupled with most existing simulation software for different thermal mass envelope analyses to make up for differences between the multi-dimensional and one-dimensional models,simultaneously simplifying simulation calculations.

Calibration of X-ray telescope prototypes at PANTER

We report on a ground X-ray calibration of two X-ray telescope prototypes at the PANTER X-ray Test Facility, operated by the Max-Planck-Institute for Extraterrestrial Physics, in Neuried, Germany.The X-ray telescope prototypes were developed by the Institute of Precision Optical Engineering(IPOE)of Tongji University, in a conical Wolter-I configuration, using thermal glass slumping technology.Prototype #1 with three layers and Prototype #2 with 21 layers were tested to assess the prototypes’ onaxis imaging performance. The measurement of Prototype #1 indicates a Half Power Diameter(HPD) of 82′′ at 1.49 keV. As for Prototype #2, we performed more comprehensive measurements of on-axis angular resolution and effective area at several energies ranging from 0.5–10 keV. The HPD and effective area are111′′ and 39 cm^2 at 1.49 keV, respectively, at which energy the on-axis performance of the prototypes is our greatest concern.

Dynamic Characteristic Study of Ball Screw Feed Drive Systems Based on Multi-flexible Body Model

A new ball screw dynamic model was developed under the adequate consideration of the interaction in the screw-nut assembly (not only the mutual-coupling factors but also the self-coupling factors) . Based on this model,the multi-flexible body (MFB)dynamic model of ball screw feed drive system was then founded in order to take full account of the influencing factor of system flexibility and study the dynamic behaviors of the whole mechanical transmissions. Moreover,the MFB based state space modeling was proposed by modal state space method, which extraced the eigenmodes of more dominant modes and applied them into an MFB state space model,and realized the integrated model of servo drives and MFB mechanical transmissions more effectively and efficiently. In conclusion,the comparisons between simulations and experimental results show: the stiffness formulation of the ball screw assembly derived above is a suitable method for achieving accurate MFB models of ball screw mechanical transmission systems,this proposed MFB model is valid,and the integrated model of ball screw feed drive system is accurate and reliable. All these provide the important approaches and guidelines for dynamic characteristic study and selection of control parameters in the machine tool design period.

Effect of Heat Treatment on Microstructure and Mechanical Behavior of Cu-Bearing 316L Stainless Steel Produced by Selective Laser Melting

Cu-bearing stainless steels(SSs)with high strength,excellent plasticity,and effective antimicrobial properties hold significant potential for applications in the marine industry.In this study,Cu-bearing SSs with copper ranging from 0 to 6.0 wt%were successfully prepared using selective laser melting(SLM)technology.For the Cu-bearing SSs with different copper contents,the effect of heat treatment on the microstructural and mechanical behaviors was studied systematically.Microstructural observations revealed that the subgrain size of Cu-bearing SSs increased with heat treatment at 500℃ and 700℃ for 6 h.Furthermore,the tensile strength and elongation increased after the heat treatment temperature due to the combined effect of dislocations,twins,andε-Cu precipitated phases.Notably,after heat treatment at 700℃,the SLM4.5Cu sample exhibited an abnormal rise in tensile strength and elongation.This finding suggests that the diffusion strengthening caused byε-Cu precipitates exceeded the stacking fault energy.Consequently,the tensile strength and elongation reached 693.32 MPa and 56.94%,respectively.This work provides an efficient approach for preparing Cu-bearing SSs with exceptional strength and plasticity.

Modelling method of inter-building movement for campus-scale occupancy simulation:A case study

As an important factor in the investigation of building energy consumption,occupant behavior(OB)has been widely studied on the building level.However so far,studies of OB modelling on the district scale remain limited.Indeed,district-scale OB modelling has been facing the challenges from the scarcity of district-scale data,modelling methods,as well as simulation application.This study initiates the extrapolation of occupancy modelling methodology from building level to district scale through proposing modelling methods of inter-building movements.The proposed modelling methods utilize multiple distribution fittings and Bayesian network to upscale the event description methods from inter-zone movement events at the building level to inter-building movement events at the district level.This study provides a framework on the application of the proposed modelling methods for a university campus in the suburbs of Shanghai,taking advantages of data sensing,monitoring and survey techniques.With the collected campus-scale occupancy data,this paper defines five patterns of inter-building movement.One pattern represents the dominated inter-building movement events for one kind of students in their daily campus life.Based on the quantitative descriptions for various inter-building movement events,this study performs the stochastic simulation for the campus district,using Markov chain models.The simulation results are then validated with the campus-scale occupancy measurement data.Furthermore,the impact of inter-building movement modelling methods on building energy demand is evaluated for the library building,taking the deterministic occupancy schedules suggested by current building design standard as a baseline.

Numerical simulation on magnetic confinement characteristics of internal vortex electrostatic cyclone precipitator under different working voltages

Aiming at improving the capture performance of internal vortex electrostatic cyclone precipitator(ECP),a theoretical model with mechanics-electric-magnetic coupling was established,the collection efficiency of magnetic confinement ECP under different working voltages was simulated,and the influence of magnetic flux intensity on the removal performance of submicron particles was explored.Results show that the number of particles escaped from the cyclone is greatly reduced after the introduction of magnetic field and electric field,indicating that charging effect and magnetic confinement are more conductive to trap submicron particles in the internal vortex ECP.The lower the working voltage is,the worse the charging lifting effect is,but the stronger the magnetic confinement characteristics are.Furthermore,the contributions of charging effect to collection efficiency and magnetic confinement characteristics are more obvious at a weaker magnetic flux density.The research results can provide a practical new idea for the innovative design of ECP.

Surrogate modeling for long-term and high-resolution prediction of building thermal load with a metric-optimized KNN algorithm

During the pre-design stage of buildings,reliable long-term prediction of thermal loads is significant for cool-ing/heating system configuration and efficient operation.This paper proposes a surrogate modeling method to predict all-year hourly cooling/heating loads in high resolution for retail,hotel,and office buildings.16384 surrogate models are simulated in EnergyPlus to generate the load database,which contains 7 crucial building features as inputs and hourly loads as outputs.K-nearest-neighbors(KNN)is chosen as the data-driven algorithm to approximate the surrogates for load prediction.With test samples from the database,performances of five different spatial metrics for KNN are evaluated and optimized.Results show that the Manhattan distance is the optimal metric with the highest efficient hour rates of 93.57%and 97.14%for cooling and heating loads in office buildings.The method is verified by predicting the thermal loads of a given district in Shanghai,China.The mean absolute percentage errors(MAPE)are 5.26%and 6.88%for cooling/heating loads,respectively,and 5.63%for the annual thermal loads.The proposed surrogate modeling method meets the precision requirement of engineering in the building pre-design stage and achieves the fast prediction of all-year hourly thermal loads at the district level.As a data-driven approximation,it does not require as much detailed building information as the commonly used physics-based methods.And by pre-simulation of sufficient prototypical models,the method overcomes the gaps of data missing in current data-driven methods.

Modelling method for air-conditioning usage behavior in multi-occupant office space based on group decision-making strategy

Occupant behavior largely influence the energy use within buildings.In the multi-occupant office,occupant behavior is affected by individual preference as well as the interaction among occupants,and yet no suitable model is available to precisely reflect the behavior characteristics.This paper proposed and introduced a method for innovative multi-occupant air-conditioning(AC)usage behavior modelling in a multi-occupant office,which used intuitionistic fuzzy preference relationship to describe individual behavior intention and a hierarchical structure to reflect the social relationship among multiple occupants through subjective evaluation method.The group decision-making process combined the individual behavior intention and the weights of occupants using the analytic hierarchy process.Then,the AC usage behavior of a multi-occupant office was simulated by integrating the multi-occupant model into designer’s simulation toolkit(DeST)building performance simulation software.The results of conducted analysis of a single office with multi-occupant showed that the proposed multi-occupant modelling method could quantitatively characterize the group relationships and AC usage behavior patterns.The absolute errors for the total AC operation time and frequency of the start-up periods of AC between the simulation and measurement results were only 2.7%and 2.0%,respectively.Thus,the proposed multi-occupant modelling method could realize a relatively accurate simulation of the multi-occupant behavior.

High-spatial-resolution composition analysis of micro/nanostructures with a nanoscale compositional variation

The composition of materials in a micro-/nano-devices plays a key role in determining their mechanical,physical,and chemical properties.Especially,for devices with a compositional change on nanoscale which can often be achieved by point-by-point direct writing technology using a focused ion beam(FIB),electron beam(EB),or laser beam(LB),but so far,nanoscale composition analysis of a large-area micro/nano structures with a variation composition remains a big challenge in cost,simpleness,and flexibility.Here we present a feasible route to realize large-area composition analysis with nanoscale spatial resolution by using Raman spectroscopy.We experimentally verified the capability of this method by analyzing a complex Sn-SnOx system of a microscale grayscale mask with nanoscale spatial resolution of composition.Further analyses using Auger electron spectroscopy,transmission electron microscopy,and atomic force microscopy indicated the effectiveness and practicality of our method.This work opens up a way to analyze the composition of a large-area complex system at a nanoscale spatial resolution,and the method can be extended to many other material systems.

Study on the application of reinforcement learning in the operation optimization of HVAC system

Supervisory control can be used to optimize the HVAC system operation and achieve building energy conservation,while reinforcement learning(RL)is considered as a promising model-free supervisory control method.In this paper,we apply RL algorithm to the operation optimization of air-conditioning(AC)system and propose an innovative RL-based model-free control strategy combining rule-based and RL-based control algorithm as well as complete application process.We use a variable air volume(VAV)air-conditioning system for a single-storey office building as a case study to validate the optimization performance of the RL-based controller.We select control strategies with the rule-based control controller(RBC)and proportional-integral-derivative(PID)controller respectively as the reference cases.The results show that,for the air supply of single zone,the RL controller performs the best in terms of both non-comfortable time and energy costs of AC system after one-year exploration learning.The total energy consumption of AC system reduced by 7.7%and 4.7%,respectively compared with RBC and PID strategies.For the air supply of multi-zone,the performance of RL controller begins to outperform the reference strategies after two-year exploration learning and two-year buffer stage.From the seventh year on,RL controller performs much better in terms of both non-comfortable time and operating costs of AC system,while the operating cost of AC system is reduced by 2.7%to 4.6%compared with the reference strategies.In addition,RL controller is more suitable for small-scale operation optimization problems.

Additive manufacturing of metals:Microstructure evolution and multistage control

As a revolutionary industrial technology,additive manufacturing creates objects by adding materials layer by layer and hence can fabricate customized components with an unprecedented degree of freedom.For metallic materials,unique hierarchical microstructures are constructed during additive manufacturing,which endow them with numerous excellent properties.To take full advantage of additive manufacturing,an in-depth understanding of the microstructure evolution mechanism is required.To this end,this review explores the fundamental procedures of additive manufacturing,that is,the formation and binding of melt pools.A comprehensive processing map is proposed that integrates melt pool energy-and geometry-related process parameters together.Based on it,additively manufactured microstructures are developed during and after the solidification of constituent melt pool.The solidification structures are composed of primary columnar grains and fine secondary phases that form along the grain boundaries.The post-solidification structures include submicron scale dislocation cells stemming from internal residual stress and nanoscale precipitates induced by intrinsic heat treatment during cyclic heating of adjacent melt pool.Based on solidification and dislocation theories,the formation mechanisms of the multistage microstructures are thoroughly analyzed,and accordingly,multistage control methods are proposed.In addition,the underlying atomic scale structural features are briefly discussed.Furthermore,microstructure design for additive manufacturing through adjustment of process parameters and alloy composition is addressed to fulfill the great potential of the technique.This review not only builds a solid microstructural framework for metallic materials produced by additive manufacturing but also provides a promising guideline to adjust their mechanical properties.

Stable noise-like pulse generation in all-PM mode-locked Tm-doped fiber laser based on NOLM

A stable noise-like(NL)mode-locked Tm-doped fiber laser(TDFL)relying on a nonlinear optical loop mirror(NOLM)was experimentally presented.Different from the previous NL mode-locked TDFL with NOLM,the entire polarization-maintaining(PM)fiber construction was utilized in our laser cavity,which makes the oscillator have a better resistance to environmental perturbations.The robust TDFL can deliver stable bound-state NL pulses with a pulse envelope tunable from〜14.1 ns to〜23.6 ns and maximum pulse energy of〜40.3 nj at a repetition rate of〜980.6 kHz.Meanwhile,the all-PM fiber laser shows good power stability[less than〜0.7%)and repeatability.

Virtual simulation of production line for ergonomics evaluation

To avoid ergonomic problems in the early planning stages of a production line and achieve more satisfactory planning and design, ergonomic simulation is particularly important in digital production line planning. An ergonomics analysis method is presented by using two theories： Ovako working posture analysis system （OWAS） and Burandt-Schultetus hand-arm force analysis （BSHA）. The processes of ergonomics analysis and simulation are discussed based on a platform of process simulation and process designer. As an example, the paper shows how ergonomics problems are considered in production line planning to make a better choice between different production line planning schemes.

0.33 mJ, 104.3 W dissipative soliton resonance based on a figure-of-9 double-clad Tm-doped oscillator and an all-fiber MOPA system

We demonstrate, for the first time, to the best of our knowledge, an all-fiber figure-of-9 double-clad Tm-doped fiber laser operating in the dissipative soliton resonance(DSR) regime. Stable mode-locked rectangular pulses are obtained by using the nonlinear amplifying loop mirror(NALM) technique. A long spool of high-nonlinearity fiber(HNLF) and a segment of SMF-28 fiber are used to enhance the nonlinearity of the NALM loop and to obtain a large all-anomalous regime. Output power and pulse energy are further boosted by using a three-stage master oscillator power amplifier(MOPA) system. At the maximum pump power, average output power of up to 104.3 W with record pulse energy of 0.33 mJ is achieved with a 2 μm DSR-based MOPA system.

Chatter identification of thin-walled parts for intelligent manufacturing based on multi-signal processing

Machine chatter is still an unresolved and challenging issue in the milling process,and developing an online chatter identification and process monitoring system towards smart manufacturing is an urgent requirement.In this paper,two indicators of chatter detection are investigated.One is the real-time variance of milling force signals in the time domain,and the other one is the wavelet energy ratio of acceleration signals based on wavelet packet decomposition in the frequency domain.Then,a novel classification concept for vibration condition,called slight chatter,is proposed and integrated successfully into the designed multi-classification support vector machine(SVM)model.Finally,a mapping model between image and chatter indicators is established via a distance threshold on the image.The multi-SVM model is trained by the results of three signals as an input.Experiment data and detection accuracy of the SVM model are verified in actual machining.The identification accuracy of 96.66%has proved that the proposed solution is feasible and effective.The presented method can be used to select optimized milling parameters to improve machining process stability and strengthen manufacturing system monitoring.

Homogenization heat treatment for an additively manufactured precipitation-hardening high-entropy alloy

A precipitation-hardening high-entropy alloy(HEA),(FeCoNi)_(86)Al_(7) Ti_(7),was successfully fabricated using selective laser melting(SLM).Severe segregation of Ti occurred at the boundaries of dislocation cells.Therefore,homogenization heat treatment at 1150℃for 0.5 h was performed to alleviate the microsegregation.After homogenization,almost no dislocation cells were left in the grains,and recrystallization occurred as the average grain size increased from 37 to 54μm.Compared with the initial as-built HEA,the ductility of the HEA increases significantly from 29%to 40%,and the strength decreases slightly from 710 to 606 MPa.For further aging,pre-homogenization can decrease the precipitation of ordered L2_(1) phases.Because void has a high propensity to initiate from the matrix/L2_(1) incoherent interface,pre-homogenization reduced the number of weak points,thus considerably improving the plastic deformation ability of the aged HEA by 36%.In addition,the strengthening mechanism has also been analyzed for the aged HEA.It was revealed that the coherent L1_(2)precipitate contributed the most to the increased strength.