A NARX Model to Predict Cabin Air Temperature to Ameliorate HVAC Functionality

Vehicular technology has integrated many features in the system, which enhances the safety and comfort of the user. Among these features, heating, ventilation, and air conditioning (HVAC) is the only feature that maintains the set cabin air temperature (CAT). The user’s command drives the set CAT, and the thermostat provides feedback to the HVAC to maintain the set CAT. The CAT is increased by extracting the heat from the engine surface produced by the fuel combustion, whereas the CAT is reduced by the known processes of the air conditioning system (ACS). Therefore, the CAT driven by the user’s command may not be optimal, and estimating the optimal CAT is still unsolved. In this work, we propose a new process where the user can input a range for CAT instead of a single value. Optimal HVAC criteria were defined, and the CAT was estimated by performing iterative analysis in the user-selected range satisfying the criteria. The HVAC criteria were defined based on two measurable parameters: air conditioning refrigerant fluid pressure (ACRFP) and engine surface temperature (EST) empirically defined as the vector CATOP. In this article, a NARX DL model was used by mapping the vehicle-level vectors (VLV) to predict the CATOP in real-time using field data obtained from a 2020 Cadillac CT5 test vehicle. Utilising the DL model, CATOP for future time steps was predicted by varying the CAT in the definite range and applying HVAC criteria. Thus, an optimal set CAT was estimated, corresponding to the optimal CATOP defined by the HVAC criteria. We performed the validation of the DL model for multiple datasets using traditional statistical techniques, namely, signal-to-noise ratio (SNR) values, first-order derivatives (FOD), and root-mean-square error (RMSE).

“That’s Just a Part of Growing Up”: A Study of Non-formal Educators’ Lay Theories of Adolescence

This instrumental case study explored non-formal educators’ lay theories of adolescence using the case of the Boy Scouts of America’s Scouts BSA program, a co-ed program serving youth between the ages of 11 and 17. We conducted an iterative analysis of 110 structured interviews with Scouts BSA adult volunteer leaders who served as scoutmasters or assistant scoutmasters. Results indicated that participants discussed adolescence in terms of youth characteristics as well as processes youth underwent during their adolescent years. These adults sometimes viewed adolescence as idiosyncratic, identifying differences in learning, behavior, and family situations among youth, particularly those whom they had identified as exhibiting specific challenges like autism. The results also illustrated relationships between the program and lay theories of adolescence. Namely, core Scouts BSA programmatic structures and expectations such as operating the patrol/troop method hierarchies, building leadership skills, camping or outdoor activities, and including all youth in activities influence participants’ own views of adolescence, including their views of adolescence as a time to cultivate maturity and independence. The study concludes with a brief discussion of results and limitations of the study, including recommendations for training and additional research.

A NARX model to Predict Cabin Air Temperature to Ameliorate HVAC Functionality

The vehicular technology has integrated many features in the system, which enhances the safety and comfort of the user. Among these features, heating, ventilation, and air conditioning (HVAC) is the only feature that maintains the set cabin air temperature (CAT). The user’s command drives the set CAT, and the thermostat provides feedback to the HVAC to maintain the set CAT. The CAT is increased by extracting the heat from the engine surface produced by the fuel combustion, whereas the CAT is reduced by the known processes of the air conditioning system (ACS). Therefore, the CAT driven by the user’s command may not be optimal, and estimating the optimal CAT is still unsolved. In this work, the user was allowed to input a range for CAT instead of a single value. Optimal HVAC criteria were defined, and the CAT was estimated by performing iterative analysis in the user-selected range satisfying the criteria. The HVAC criteria were defined based on two measurable parameters: air conditioning refrigerant fluid pressure (ACRFP) and engine surface temperature (EST) empirically defined as the vector CATOP. In this article, a NARX DL model by mapping the vehicle-level vectors (VLV) to predict the CATOP in real-time using field data obtained from a 2020 Cadillac CT5 test vehicle. Utilising the DL model, CATOP for future time steps were predicted by varying the CAT in the definite range and applying HVAC criteria. Thus, an optimal set CAT was estimated, corresponding to the optimal CATOP defined by the HVAC criteria. We performed the validation of the DL model for multiple datasets using traditional statistical techniques, namely, signal-to-noise ratio (SNR) values, first-order derivatives (FOD), and root-mean-square error (RMSE).

Office Worker Perspective on an Artificial Intelligence Workstation: A Qualitative Study

Date Presented Accepted for AOTA INSPIRE 2021 but unable to be presented due to online event limitations. This study explored office workers' perspectives on including artificial intelligence (AI) in their office workspace. Following an iterative analysis of six focus-group interviews with a total of 45 participants, three constructs emerged. Rich discussions demonstrated how acceptability of an AI workstation is complex and affected by the person, context, and their occupations. Primary Author and Speaker: Yoko E. Fukumura Contributing Authors: Julie McLaughlin Gray, Gale Lucas, Burcin Becerik-Gerber, and Shawn C. Roll

Study on allocation and realization method of helicopter vulnerability index

To reduce the vulnerability of attack helicopters under fragment/projectile strikes, the method of assigning vulnerability index from the whole aircraft to critical components under single and multiple attacks is mainly studied. Under a single strike, the system components in the same direction are divided into three situations: no component overlap, nonredundant model with component overlap and redundant model with component overlap. Two index allocation methods based on the ratio of the presented area of the critical components and the ratio of the vulnerability assessment results of the critical components are proposed. The system components are divided into redundant components and non-redundant components, and an index allocation method based on the proportion of critical components' vulnerability results is proposed under multiple strikes. On this basis, combining with the vulnerability reduction measures of attack helicopters, the vulnerability index requirements of corresponding components are achieved through iterative analysis. Finally, the AH-64D helicopter is subjected to simulation tests under single and multiple strikes, and the vulnerability indexes of B-level and C-level are assigned, which verified the feasibility of the method.

Development of Optimal Design Method for Steel Double-Beam Floor System Considering Rotational Constraints

Under high gravity loads, steel double-beam floor systems need to be reinforced by beam-end concrete panels to reduce the material quantity since rotational constraints from the concrete panel can decrease the moment demand by inducing a negative moment at the ends of the beams. However, the optimal design process for the material quantity of steel beams requires a time-consuming iterative analysis for the entire floor system while especially keeping in consideration the rotational constraints in composite connections between the concrete panel and steel beams. This study aimed to develop an optimal design method with the LM (Length-Moment) index for the steel double-beam floor system to minimize material quantity without the iterative design process. The LM index is an indicator that can select a minimum cross-section of the steel beams in consideration of the flexural strength by lateral-torsional buckling. To verify the proposed design method, the material quantities between the proposed and code-based design methods were compared at various gravity loads. The proposed design method successfully optimized the material quantity of the steel double-beam floor systems without the iterative analysis by simply choosing the LM index of the steel beams that can minimize objective function while satisfying the safety-related constraint conditions. In particular, under the high gravity loads, the proposed design method was superb at providing a quantity-optimized design option. Thus, the proposed optimal design method can be an alternative for designing the steel double-beam floor system.