Adaptive kinetic architecture has emerged from a need for innovative designs that adapt to the environment and changing needs of the occupants. Architectural design and modes of egress are critical in an emergency. Flocking describes a certain collective behavior where agents are brought together in groups and move as a cohesive unit from place to place. Collective behavior may be observed in microscopic as well as macroscopic environments. Crowd modeling incorporates the study of human behavior, mathematical modeling, and molecular or fluid dynamics. The simulation of agents and their movement in the built environment is beneficial for design professionals, scientists, and engineers. Human behavior in panic situations is notably similar to fluids and molecules. The objective of this research was to evaluate the movement of agents in buildings using discrete dynamic simulation. We used a novel discrete molecular dynamics technique to simulate the evacuation of agents in panic situations. Various adaptive geometric configurations were analyzed for improved crowd flow. Kinetic walls were modeled in order to evaluate design optimization as it relates to rates of egression. This research proposes the use of kinetic walls to improve safety and efficiency during an emergency evacuation. Adaptive geometric configurations show improvements over the conventional design framework.

A manual material handling task involves the phases of reaching, lifting, unloading, and standing up (RLUS). Understanding the mechanisms of manual material handling is important for occupational health and the development of assist devices. Predictive models are becoming popular in exploring which performance criterion is appropriate in the lifting phase. However, limited attempts have been performed on the other phases. The associated performance criterion for predicting other phases is unknown. In this study, an optimization model for predicting RLUS has been developed with the multi-objective optimization method. Two performance criteria (minimum dynamic effort and maximum balance) were studied to explore their importance in each phase. The result shows that maximum balance leads to joint angle errors 27.6% and 40.9% smaller than minimum dynamic effort in reaching and unloading phases, but 40.4% and 65.9% larger in lifting and standing up phases. When the two performance criteria are combined, the maximum balance could help improve the predicting accuracy in the reaching, lifting, and unloading phases. These findings suggest that people prefer different performance criteria in different phases. This study helps understand the differences in motion strategies in manual materials handling (MMH), which would be used to develop a more accurate predictive model.

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Background: The anterior cruciate ligament (ACL) is one of the most injurious parts of the knee in the biomechanical environment during landing actions. The purpose of this study was to compare the lower limb differences in movement patterns, muscle forces and ACL forces during drop landing (DL), drop vertical jump (DVJ) and forward vertical jump (FVJ).Methods: Eleven basketball and volleyball female college athletes (Division II and I) were recruited. Landing actions of DL, DVJ and FVJ, kinematics and dynamics data were collected synchronously using a motion capture system. OpenSim was used to calculate the ACL load, knee joint angle and moment, and muscle force.Results: At initial contact, different landing movements influenced knee flexion angle; DL action was significantly less than FVJ action (p = 0.046). Different landing actions affected quadriceps femoris forces; FVJ was significantly greater than DL and DVJ actions (p = 0.002 and p = 0.037, respectively). However, different landing movements had no significant effects on other variables (knee extension moment, knee valgus angle and moment, hamstring and gastrocnemius muscle forces, and ACL forces) (p > 0.050).Conclusion: There was no significant difference in the knee valgus, knee valgus moment, and the ACL forces between the three landing actions. However, knee flexion angle, knee extension moments sagittal factors, and quadriceps and gastrocnemius forces are critical factors for ACL injury. The DL action had a significantly smaller knee flexion angle, which may increase the risk of ACL injury, and not recommended to assess the risk of ACL injuries. The FVJ action had a larger knee flexion angle and higher quadriceps femoris forces that were more in line with daily training and competition needs. Therefore, it is recommended to use FVJ action in future studies on risk assessment of ACL injuries and injury prevention in female college athletes.

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