The design freedom enabled by additive manufacturing, combined with the unique properties of generative lattice structures, has gained increasing attention in thermal system technologies, especially for the development and fabrication of heat exchangers. In this study, a hybrid heat exchanger was developed by integrating a Diamond unit cell, known for its high thermal performance, with an IWP unit cell, which offers low flow resistance. The goal is to reduce flow resistance while maintaining heat transfer efficiency. A physical model was simulated using ANSYS software to evaluate the heat exchanger’s performance. The results indicate that integrating IWP cells into a Diamond unit cell structure effectively reduces flow resistance, though with a slight compromise in heat transfer performance. This balance provides a viable design strategy for heat exchangers in applications requiring precise flow resistance control.

This paper presents a comprehensive approach for reliability assessment and optimization of ball joints by combining finite element analysis (FEA) method with machine learning algorithms, in particular by exploiting the power of the XGBoost machine learning algorithm. FEA simulations were carried out using ANSYS to generate a dataset encompassing various solder joint geometrical parameters configurations. Key input parameters, including geometric dimensions, were identified by sensitivity analysis and used as features for training the XGBoost model. The trained model demonstrated solid performance. Feature importance analysis revealed critical factors influencing solder joint reliability and provided insights for optimization strategies. This research provides practical recommendations for optimizing solder joint and material design to improve reliability and performance in electronic packaging applications.

Additive manufacturing processes and generative lattice structure are two increasingly popular methods in thermal management applications, particularly in the design and production of heat sinks for electronic devices. In this paper additive manufacturing was used to create heat sinks with lattice structures, specifically triple periodic minimum surfaces (TPMS). Where a conventional pin-fin heat conductor was compared with a heat sink using TPMS lattices, including Gyroid, IWP, and Neovius structures, by evaluating thermal performance. A model was physically simulated to study the thermal performance of the dispersants on the ANSYS software. The results show that the heat sink incorporating TPMS lattices exhibits superior thermal performance than the traditional pin heat sink. The research demonstrates the potential of additive manufacturing to create complex geometries that can improve the thermal dissipation of electronic devices.

The biological effects of radiation is one of the current interests studies of biologists, doctors and most laboratories of health care. Several papers have analyzed the effects of ionizing radiations or for non-ionizing radiations that we may attend in all domains. In fact we are exposure to many sources of both types. Therefore the analyze their effect depends on the absorbed dose rate of the radiation on human body. it is measured by the energy absorbed according to the ionizing radiation and the electric field to the non-ionizing ones. The waves of all radiations are as a heat source that penetrates the surface that are converted into thermal energy within the material. Therefore The mathematical models of the absorbed dose by Ionizing or Non Ionizing equation consist in bio heat and thermal equation also in dielectric properties which allow us to describe temperature as function of SAR distributions in the human body exposed to both radiations simultaneously. In this study, the 2-D computational analysis is used to study the distribution of the total specific absorption rate (SAR) according to temperature on human's organ exposed to ionizing radiation and the non ionizing one.

Cell phones and all radio transmitters become unavoidable in our daily life. Several debates held on the effects of the waves emitted by these equipment on human health especially that emitted by base stations. Therefore several studies have estimated the electric field emitted by stations in order to analyze the specific absorption rate on the human body of these waves. But the problematic is that the electric field which is one of SAR parameter's calculation, it varies with time, which prevents us to determine a concrete value of the fields, which the human body is exposed in a geographical area. The purpose of this paper is to determine the value of the weighted electric field and the specific absorption rate in a geographical area, by modeling the measured values of E fields in this area by fuzzy systems.

The Internet of Things (IoT) is an important part of the information technology of the future. Technically, IoT is expected to enable people-thing and thing-thing interconnections by combining communication technologies and networks. Our Lab has been actively promoting research on 5G & IoT, in which the NB-IoT new radio interface issue is of great interest. New 5G tests put forward a lot of requirements for new radio interface in terms of service bandwidth, power consumption, as well as the number of connections for IoT performance management. Based on Morocco's current situation, this article first discusses the 5G vision, Furthermore, we will introduce IoT SoftRadio tool, NB-IoT UEs sharing scenarios are summarized. Finally, based on the current framework of NB-IoT radio performance management according to first Africa and Morocco NB-IoT Experimental Results and Deployment Scenario, potential services classification and air interface assessment are proposed to accommodate new 5G & IoT performances.