An intelligent HVAC control strategy for supplying comfortable and energy-efficient school environment

In South Korea, school buildings require significant energy inputs for heating and air-conditioning, and the majority of the occupants are adolescent students, whose health and cognitive performance are vulnerable to poor indoor air quality (IAQ) and thermal discomfort. Using field measurements, some previous studies have reported that some Korean schools have poor IAQ and thermal conditions. Thus, it is necessary to develop effective heating, ventilation, and air-conditioning (HVAC) control strategies to improve the indoor environment and reduce energy consumption. Therefore, this study proposes an intelligent HVAC integrated control strategy that can improve indoor environmental quality (IEQ) and reduce energy consumption in school buildings. The proposed strategy utilizes an integrated neural network prediction model for IEQ and a heuristic method that can optimize control objectives (i.e., the predicted mean vote [PMV], carbon dioxide [CO₂], particulate matter with diameters of 10 and 2.5 μm [PM₁₀ and PM_2.5, respectively], and HVAC energy consumption). To evaluate the control performance of the proposed strategy, the present study employs two base algorithms (i.e., a rule-based and a non-adaptive control approach) under non-disturbance and forcing disturbance scenarios. The control failure period for PMV is found to be 1.6420% and 9.4773% of the total occupancy period under the non-disturbance and forcing disturbance scenarios, respectively, while CO₂ control failure does not occur under either scenario. The control failure periods for PM₁₀ and PM_2.5 were 5.1676%, and 7.1844%, respectively, under forcing disturbance. Under the non-disturbance scenario, the proposed strategy consumed 2,467.07 kWh and 870,26 kWh for heating and cooling, respectively, representing 91.1% and 84.08% of that for the rule-based algorithm. The proposed strategy can thus effectively improve the IEQ of a building and has the potential for use in the development of integrated environmental management solutions for buildings.     

Effects of ultrasonic vibration assisted milling with laser ablation pretreatment on fatigue performance and machining efficiency of SiCf/SiC composites

Due to the poor machinability of SiC_f/SiC parts in machining, many problems are caused, such as low machining efficiency, poor machining quality and high processing cost, which seriously limit its manufacturing and application. A novel process ultrasonic vibration assisted milling with laser ablation pretreatment (UVAMLAP) was proposed to optimize the fatigue performance and machining efficiency of SiC_f/SiC parts. This process was used to fabricate specimens, which were then tested for tensile strength and fatigue performance. The results show that UVAMLAP could enhance surface quality, and increase the tensile strength and residual tensile strength of the sample by 9.4% and 13.5%. This process can avoid damage aggravation in the initial stage of failure, weaken matrix fracture and interface debonding velocity, and reduce fatigue performance degradation caused by machining damage. In addition, comprehensive evaluation based on multi-dimensional indicators such as milling quality, machining efficiency and tool cost for machining strategy was carried out by taking tensile sample machining as an example. The UVAMLAP process can not only improve the machined surface quality, but also reduce the machining time by 31.3% and the tool cost by 75%. Therefore, UVAMLAP provides a feasible process scheme for high-efficiency and low-damage machining of SiC_f/SiC parts.     

A novel evolutionary analysis model for social collaborative design ecosystem based on information entropy

Social collaborative design rooted in online platforms has emerged as a new paradigm for product innovation, with open and dynamic design elements bringing about external design resources and internal fluctuations. To guarantee sustainable operation of the design system, assessing the impact of the uncertainty of the external environment and randomness of the internal organization on the efficiency and stability of the system’s operation is essential. To that end, this paper proposes a quantitative evolutionary analysis model based on information entropy theory to assess the benefits and drawbacks of system evolution by measuring the degree of development and harmony of the system, as well as to anticipate future evolutionary trajectories using a classical time-series prediction model. The accuracy and validity of the model were verified using 794,509 design data points accumulated over 10 years on the Zhubajie platform, the largest social collaborative design platform in China. In summary, our study provides a method for stakeholders to evaluate the evolutionary trend of the design ecosystem. Platform managers can utilize this model for controlling the operating state of the system to ensure safe and effective operation.     

Effect of hydrogen on the microstructure and mechanical properties of high temperature deformation of Ti6Al4V additive manufactured

The additive manufactured Ti6Al4V-xH titanium alloy was compressed at 600°C–750 °C on a Gleeble 3800 testing machine, and the compression rates were 1s⁻¹ and 0.01s⁻¹, respectively. The experimental results show that with the increase of hydrogen content, the flow stress of the alloy decreases firstly and then increases gradually. When the hydrogen content is 0.27 wt%, the flow stress of titanium alloy is the smallest. EBSD and TEM analysis were carried out and show that the α lamellar microstructure became larger at 0.27H, the corresponding flow stress also decreased, and slip bands appeared in the alloy. Dislocation slip was an important deformation mechanism of the alloy. When the hydrogen content continued to increase, the α phase in the alloy gradually decreased, and α″ appeared at 0.81H. Therefore, adding appropriate hydrogen can reduce the alloy flow stress and improve the performance of titanium alloy during hot deformation.     

TC17(α + β)/TC17(β)钛合金线性摩擦焊接头相组成及织构分析

利用电子背散射衍射技术对TC17(α+β)/TC17(β)钛合金线性摩擦焊接头测试并分析,对接头各区域进行相鉴定和织构分析.结果表明,与母材相比,焊态接头两侧热力影响区α相减少,β相增多.由于焊缝区冷却迅速快,焊态焊缝处发生动态再结晶,生成了大量的亚稳定β相晶粒. TC17(β)侧母材及热力影响区的织构分布密度比TC17(α+β)侧强,且焊态焊缝区产生(5 4 6)[■]织构,轧面与(1 1 1)近似平行.经过610℃热处理后,焊缝区亚稳定β相发生分解,形成细小的次生α相和β相.与焊态焊缝相比,热处理后焊缝区晶体稍有转动,焊缝区织构强度较焊态有较大增强,形成(5 5 7)[■]织构.热处理前后的焊缝区晶体取向都存在着ND方向与[1 1 1]靠近,轧面与(111)接近平行的择优取向.     

Member combination selection for product collaborative design under the open innovation model

A temporary product collaborative design team (PCDT) formed by customers and candidate service providers is the main organization form required to complete the task of product collaborative design (PCD) under the open innovation model. Therefore, the aim of this study was to implement synergy effect-based member combination selection (SE-MCS) while ensuring customer participation in the PCD. First, the conceptual framework of SE-MCS method was developed to characterise the SE-MCS process that includes the customer. Second, SE-MCS indicators were determined by analysing the characteristics of PCD under the open innovation model, and the quantitative calculation methods for these indicators were provided. Subsequently, the mathematical model for SE-MCS considering customer participation was established, and a multi-objective optimisation algorithm was adopted to identify the optimal scheme. Finally, the formation of a design team for a beach waste collection vehicle was performed to verify the proposed method. The results showed that the proposed method is more suitable to implement SE-MCS of PCD under the open innovation model. It can facilitate the smooth operation of PCD tasks and improve the quality and efficiency of teamwork, thereby increasing customer satisfaction.     

Synthesis of single-phase high-entropy diboride powders and their spheroidization process

Spherical (Zr_.2Ti_.2Ta_.2Nb_.2Mo_.2)B₂ powders with a uniform particle size distribution are successfully prepared using a novel industrial approach, which combines spray-drying process and thermal plasma sintering technology together. In this, single-phase (Zr_.2Ti_.2Ta_.2Nb_.2Mo_.2)B₂ powders are first synthesized via a borothermal reduction process using a mixture of individual metallic oxides and boron powders as starting materials. The influence of boron powder content on the structure of prepared powders is researched. Then, (Zr_.2Ti_.2Ta_.2Nb_.2Mo_.2)B₂ granules are prepared after wet-grinding and spray-drying process, which exhibit a spherical shape and homogeneous element distribution. RF induction thermal plasma is finally used to sinter the granulated particle, and the apparent density of sintered spherical powders is increased to 2.57 g/cm³ from 1.43 g/cm³. Such powders are in potential demand for additive manufacturing techniques, and the successful synthesis of spherical (Zr_.2Ti_.2Ta_.2Nb_.2Mo_.2)B₂ powders may guide the way toward the preparation of many other spherical high-entropy diboride powders.     

A decision framework for cultural and creative products based on IF-TODIM method and group consensus reaching model

Along with increasing the emphasis on cultural attributes, product design is not only satisfied with the realization of function and appearance, but also considers the embodiment of human emotion and social style. As a result, the number of creative product based on cultural style is increasing. However, existing product decision studies do not consider this style-oriented product- ranking problem, ignore the influence of cultural style and fuzzy decision-making environment on the limited psychological behavior of decision makers (DMs). Decision is a worthwhile research topic in order to facilitate ranking for cultural and creative products (CCPs). Therefore, this paper provides a decision framework based on intuitionistic fuzzy TODIM (IF-TODIM) method and group consensus reaching (GCR) model to fill this gap. Benefit from the theory of intuitionistic fuzzy set, IF-TODIM method can deal with the limited psychological behavior of DMs and the fuzziness of decision environment. This method bases on CCPs characteristics and cultural hierarchy theory (CHT) to select the decision criteria, and applies IF-TODIM method to quantify the relationship of DMs’ preferences and establish the dominance matrix for the alternatives. Furthermore, the GCP model is introduced to improve the group consensus of DMs, and the modified overall dominance matrixes are adopted to determine the alternatives scores and ranking results. The new Chinese style decorations are used as a case study to demonstrate the practicality and feasibility of the proposed method. Moreover, comparing with IF-TOPSIS method are further to verify its effectiveness and superiority.     

TC17钛合金嵌入式线性摩擦焊接头组织与性能

针对航空长形整体构件锻造与加工的难题,提出采用嵌入式线性摩擦焊方法进行分段组合制造,采用嵌入式线性摩擦焊技术开展了TC17钛合金试验件的焊接,针对所形成的V形接头,分析了接头塑性流动规律与接头形成机理、组织特征与力学性能.?结果表明,焊接过程中,金属流动规律与普通线性摩擦焊接头有显著区别,高温塑性金属随着楔块的移动逐渐...     

Detecting anomalies and de-noising monitoring data from sensors: A smart data approach

When monitoring safety levels in deep pit foundations using sensors, anomalies (e.g., highly correlated variables) and noise (e.g., high dimensionality) exist in the extracted time series data, impacting the ability to assess risks. Our research aims to address the following question: How can we detect anomalies and de-noise monitoring data from sensors in real time to improve its quality and use it to assess geotechnical safety risks? In addressing this research question, we develop a hybrid smart data approach that integrates Extended Isolation Forest and Variational Mode Decomposition models to detect anomalies and de-noise data effectively. We use real-life data obtained from sensors to validate our smart data approach while constructing a deep pit foundation. Our smart data approach can detect anomalies with a root mean square error and signal-to-noise ratio of 0.0389 and 24.09, respectively. To this end, our smart data approach can effectively pre-process data enabling improved decision-making and the management of safety risks.