Stimulus discriminability and conditioning-history effects on response summation

Changes in task demands can have delayed adverse impacts on performance. This phenomenon, known as the workload history effect, is especially of concern in dynamic work domains where operators manage fluctuating task demands. The existing workload history literature does not depict a consistent picture regarding how these effects manifest, prompting research to consider measures that are informative on the operator's process. One promising measure is visual attention patterns, due to its informativeness on various cognitive processes. To explore its ability to explain workload history effects, participants completed a task in an unmanned aerial vehicle command and control testbed where workload transitioned gradually and suddenly. The participants’ performance and visual attention patterns were studied over time to identify workload history effects. The eye-tracking analysis consisted of using a recently developed eye-tracking metric called coefficient K , as it indicates whether visual attention is more focal or ambient. The performance results found workload history effects, but it depended on the workload level, time elapsed, and performance measure. The eye-tracking analysis suggested performance suffered when focal attention was deployed during low workload, which was an unexpected finding. When synthesizing these results, they suggest unexpected visual attention patterns can impact performance immediately over time. Further research is needed; however, this work shows the value of including a real-time visual attention measure, such as coefficient K , as a means to understand how the operator manages varying task demands in complex work environments.

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Housing Condition Differentially Impacts Escalation of Alcohol Intake, Relapse‐Like Drinking, Anxiety‐Like Behavior, and Stress History Effects by Sex

Alcoholism Clinical and Experimental Research ◽

10.1111/acer.14540 ◽

2020 ◽

Author(s):

Kelly M. Moench ◽

Marian L. Logrip

Keyword(s):

Alcohol Intake ◽

Housing Condition ◽

Stress History ◽

History Effects

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In-Place FE Modeling of Unbonded Flexible Pipelines Capturing Pressure Stiffening and Decoupled Axial/Nonlinear Bending Stiffness

29th International Conference on Ocean, Offshore and Arctic Engineering: Volume 5, Parts A and B ◽

10.1115/omae2010-20014 ◽

2010 ◽

Author(s):

Edvin Hanken ◽

Evelyn R. Hollingsworth ◽

Lars S. Fagerland

Keyword(s):

Water Injection ◽

Bending Stiffness ◽

Axial Stiffness ◽

Fe Model ◽

Nonlinear Bending ◽

Upheaval Buckling ◽

History Effects ◽

System Integrity ◽

Non Linear ◽

Bending Behaviour

For fast track pipeline projects the need for costly installation vessels and sophisticated materials for rigid pipeline water injection systems, have made flexible pipelines a competitive alternative. They can be installed with less costly construction vessels, provide a competitive lead time and a corrosion resistant compliant material. Flexible pipelines have relative high axial stiffness and low non-linear bending stiffness which is a challenge to model correctly with FE for in-place analyses of pipelines. Whilst some FE programs can model the non-linear bending behaviour of a flexible pipeline at a given pressure, current FE tools do not include the effect of increased bending resistance as the system is pressurized. Therefore, a 3D FE model in ANSYS was developed to simulate the decoupled axial and nonlinear bending behaviour of a flexible, including the bend stiffening effect for increasing pressure. A description of the model is given in this paper. It will be demonstrated how the FE model can be used to simulate the 3D nonlinear catenary behaviour of an high pressure flexible pipeline tied into a manifold during pressurization. Due to high manifold hub loads during pressurization it is essential that such a model is capable of capturing all effects during pressurization to achieve an acceptable confidence level of the system integrity. It is also described how the FE model is used for upheaval buckling design, capturing non-linearities and load history effects that can reduce the conservatism in the design.

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