Abstract Passive prosthetic knee joints remain an attractive solution for transfemoral amputees in low-resource settings because of their low cost, mechanical simplicity, and ease of maintenance. But there are numerous commercial designs which are either relatively heavy or mechanically complex. In this work, the design, finite element analysis, material selection and fabrication of a lightweight passive prosthetic knee joint with a simple polycentric mechanism are proposed. Three candidate materials (AISI 4130 steel, Al2024-T4 and Al7075-T651) were selected and experimentally characterized by tensile testing and numerically compared in terms of stress distribution, deformation, weight and factor of safety and subjected to an extreme static loading of 1000 N. The maximum of von Mises stress obtained from the finite element calculations for all materials studied was 40.2 MPa, which was found to be below their respective yield strengths, thus providing sufficient structural integrity. Al7075-T651 was found to have the highest factor of safety (12.19), minimum structural deformation (0.0497 mm) and a good strength-to-weight ratio, thus showing the best overall performance among the materials evaluated, and the least prototype weight (198 g). The prototype weight was measured and compared with the CAD weight prediction (195 g), and good agreement was obtained with the fabricated prototype (198 g), with a deviation of 1.5%. This agreement indicates that the overall geometry, volume and assigned material density are consistent in the CAD model. The entire prototype was produced at an estimated cost of about USD 160, which is considerably less expensive than many passive prosthetic knee joints on the market. This proposed design is lightweight, has sufficient structural strength, a simple mechanical structure, and a low manufacturing cost, which make it a promising alternative for making transfemoral prostheses, especially in developing and resource-limited countries.
Abstract Ground heave is known for its strong sensitivity to moisture changes, which often leads to volume variations responsible for damage to foundations, pavements, and light structures. While cement stabilization and fibre reinforcement have been widely studied, the combined use of recycled polypropylene (PP) sweeper brush filaments with lime–pozzolana cement (LPC) remains relatively unexplored, particularly for marl–clay soils. This study examines how this combined stabilization approach influences both the swelling behavior and mechanical response of two high-plasticity expansive soils. PP were added at contents ranging from 0.1 to 1.8%, with fibre lengths between 12 and 48 mm, while the LPC content varied from 1 to 18% by dry weight. A series of laboratory tests was carried out to evaluate performance. The findings show that adding fibres and binder decreased swelling. Additionally, fibres tend to alter the stress-strain response. However, in some cases, peak compressive strength dropped, most likely due to interactions of the fibres and the cemented soil. The results imply that, when paired with cementitious stabilization, PP can function as a substitute reinforcing material. However, further study is needed to enhance the combination and assess long-term performance before genuine field applications can be completely addressed.
Abstract The current study provides a techno-economic and environmental assessment of three different power supply options of the Al-Khwarizmi Building at the Applied Science Private University in Amman, Jordan. These options include conventional power generation through gas firing, gas firing of an Internal Combustion Engine, as well as solid biomass firing of an Organic Rankine Cycle system. Results have been obtained through a monthly quasi-static energy balance modelling approach (using full-load nominal performance parameters for the ICE/ORC units), which was conducted in consideration of the extreme climatic effects of Amman. A comparative study was conducted based on key annual parameters, including fuel usage, CO 2 emissions, operating costs, and power production. This suggests that the ICE system is the most feasible and cost-effective alternative, with an approximate 47.5% reduction in annual operating costs and a 27.3% reduction in CO 2 emissions compared to the traditional system. Although the ORC system is more environmentally friendly under the assumption of utilizing biomass with the consideration of the carbon neutral method, its higher installation costs, with the complication of biomass handling, render the ICE system preferable.
Abstract Harvesting fragile fruits like strawberries is still a major engineering challenge in modern greenhouse agriculture due to human expenses and crop losses. In this practical study, a four-degree-of-freedom PPPR (prismatic–prismatic–prismatic–revolute) Cartesian robotic system and a customized end-effector were designed for effective strawberry harvesting. The vibration characteristics of the system were investigated using Finite Element Analysis (FEA). A Brüel & Kjaer (B&K) Type 4514 accelerometer was used as the reference sensor, while the inbuilt Inertial Measurement Unit (IMU) of the Intel RealSense D435i camera was used as an active vibration measurement source. Using both sensor systems, experimental vibration data from robotic motion experiments were obtained and compared. The findings demonstrated that, with relative errors below 2% when compared to the reference sensor, the IMU identified prominent resonance frequency components at about 5.12 Hz, 6.12 Hz, and 6.56 Hz. For the X , Y , and Z axes, the Pearson correlation coefficients between the IMU and reference data in the time domain were 0.985, 0.968, and 0.926, respectively. Based on the obtained results, the embedded IMU was able to identify the dominant resonance frequencies observed in the reference measurements. However, the sensor's 100 Hz sampling rate continues to limit its performance.
Abstract Low latency and energy-efficient design are important requirements for Reinforcement Learning (RL) algorithms deployed on embedded and edge computing systems. Software based Q-learning shows increased power consumption as well as the overhead of sequential execution. The paper shows an energy-efficient FPGA architecture for the Q-learning update based on High Level Synthesis (HLS). An FPGA accelerator targeting the device platform Xilinx Zynq-7000 (xc7z020clg400-1) has been designed and implemented. Loop pipelining and precision fine-tuning design techniques were applied to optimize the architecture. This improvement was achieved by 50 percent as a baseline architecture got a latency of 14 cycles, which was reduced to 7 cycles when the architecture was pipelined with loops. A relative comparison of fixed point (ap_fixed<16,8>) and floating point implementations has shown that the floating point arithmetic increases the number of LUTs used by 4 times, the number of DSPs used by more than 2 times, and the delay by 29 cycles. Post implementation power analysis for fixed-point architecture shows that its energy consumption is about 4 times less per Q-update operation than a floating-point design. The results show that pipelined fixed-point FPGA architectures are a good solution to speed up the reinforcement learning process in resource-limited embedded systems.
