Bowman Model Research Articles

Structuring First-Year Retention at a Regional Public Institution: Validating and Refining the Structure of Bowman’s SEM Analysis

Structural equation modeling (SEM) considering how students’ non-cognitive attributes influence first-year college student persistence remain extraordinarily rare—as are studies that test and expand upon published structural models or studies that include college student food security. This study addresses each. We surveyed “Beginner” Freshmen, capturing eight non-cognitive measurements and ussing institutional data on performance and fall-to-fall persistence measures, we then tested the structure of Bowman et al.’s (Res High Educ 60:135–152, 2019) SEM model. In Model 1, we mimic the Bowman model’s financial variable by only including financial stress. We confirm that Bowman is a good structural model of student persistence, although our data were collected for another purpose, using different scales for non-cognitive elements and even one different non-cognitive measurement. We found students’ non-cognitive attributes remain importantly influential to social adjustment (r = .65), commitment to persist (r = .40), college GPA (r = .25), and fall-to-fall persistence (r = .30). In Model 2, we generated a latent financial security variable incorporating financial stress and food security. Including food security generated a direct influence from the financial security variable to high-school GPA (r = .25), not found in the Bowman model or Model 1, and a direct significant relationship from financial security to social adjustment (r = .11)—not found in Model 1. Further changes are observed in the indirect relationship from financial security to college GPA from Model 1 (r = .29) to Model 2 (r = .51). We highlight the robustness of the Bowman model and that the inclusion of food security brings increased strength to several relationships without sacrificing optimal fit.

Structuring First-Year Retention at a Regional Public Institution: Validating and Refining Bowman’s SEM Analysis

Structural Equation Modeling (SEM) considering how students’ non-cognitive attributes influence first-year college student persistence remain extraordinarily rare – as are studies that test and expand upon published structural models or studies that include college student food security. This study addresses each. We surveyed “Beginner” Freshmen, capturing eight non-cognitive measurements and using institutional data on performance and fall-to-fall persistence measures. We then tested the Bowman et al.’s (2019) SEM model. In Model 1, we mimic the Bowman model’s financial variable by only including financial stress. We confirm that Bowman is a good structural model of student persistence, although our data were collected for another purpose, using different scales for non-cognitive elements and even one different non-cognitive measurement. We found students’ non-cognitive attributes remain importantly influential to social adjustment (r=.65), commitment to persist (r=.40), college GPA (r=.25), and fall-to-fall persistence (r=.30). In Model 2, we generated a latent financial health variable including financial stress and food security. Including food security generated a direct influence from the financial health variable to high-school GPA (r=.25), not found in the Bowman model or Model 1, and a direct significant relationship from financial health to social adjustment (r=.11) – not found in Model 1. Further changes are observed in the indirect relationship from financial health to college GPA from Model 1 (r=.29) to Model 2 (r=.51). We highlight the robustness of the Bowman model and that the inclusion of food security brings increased strength to several relationships without sacrificing optimal fit.

Power quality analysis of DC arc furnace operation using the Bowman model for electric arc

This work is about a relatively new domain. The DC electric arc is superior to the AC electric arc and it’s not used in Romania. This is why we analyzed the work functions of these furnaces by simulation and model checking of the simulation results.The conclusions are favorable, to be carried is to develop a real-time control system of steel elaboration process.

Effect of Oxygen Inhibition on the Kinetic Constants of the UV-Radical Photopolymerization of Diurethane Dimethacrylate/Photoinitiator Systems

The kinetic constants of propagation (kp) and termination (kt) for a diurethane dimethacrylate/1-hydroxycyclohexyl phenyl ketone (Irgacure 184) system were measured using a dark polymerization technique that employs real-time FT-IR spectroscopy to measure the conversion and reaction rate of the methacrylate group at different time points. The sample was placed between two optically polished KBr plates with a 10 μm metal spacer. A series of measurements resulted in a gradual peak in the kinetic constants at a 0.15 conversion of the methacrylate group. The kinetic constants for the conversion, which ranged from 0.15 to 0.5, were used to obtain the parameters of the Anseth–Bowman model to generate a numerical simulation of the photopolymerization kinetics. The kinetic equations, the oxygen inhibition reaction-diffusion equation, and the macroradical mass balance model indicated that the gradual peak in the kinetic constant was caused by an oxygen inhibition reaction. The Anseth–Bowman model for kp and kt was...

Volt-ampere characteristics of a nitrogen DC plasma arc with anode melting

The characteristics of a nitrogen arc using a graphite cathode and a melting anode in a pilot-scale plasma furnace are investigated. The voltage is examined as a function of current and apparent plasma length. The voltage increases non-linearly with the increase of apparent plasma length, with the current fixed. The experimental data so obtained are compared with the predictions of the Bowman model for the electric arc, and with numerical simulations as well. The level of agreement between the experimental data at the melting anode and the numerical predictions confirms the suitability of the proposed the Bowman model. These characteristics are relevant to the engineering design and evaluation of a DC plasma furnace and reactor for the treatment of hazardous fly ash waste.

Electromagnetic analysis of an AC electric arc furnace including the modeling of an AC arc

PurposeThe purpose of this paper is to present a 3D finite element model of the electromagnetic fields in an AC three‐phase electric arc furnace (EAF). The model includes the electrodes, arcs, and molten bath.Design/methodology/approachThe electromagnetic field in terms of time in AC arc is also modeled, utilizing a 3D finite element method (3D FEM). The arc is supposed to be an electro‐thermal unit with electrical power as input and thermal power as output. The average Joule power, calculated during the transient electromagnetic analysis of the AC arc furnace, can be used as a thermal source for the thermal analysis of the inner part of furnace. Then, by attention to different mechanisms of heat transfer in the furnace (convection and radiation from arc to bath, radiation from arc to the inner part of furnace and radiation from the bath to the sidewall and roof panel of the furnace), the temperature distribution in different parts of the furnace is calculated. The thermal model consists of the roof and sidewall panels, electrodes, bath, refractory, and arc. The thermal problem is solved in the steady state for the furnace without slag and with different depths of slag.FindingsCurrent density, voltage and magnetic field intensity in the arcs, molten bath and electrodes are predicted as a result of applying the three‐phase AC voltages to the EAF. The temperature distribution in different parts of the furnace is also evaluated as a result of the electromagnetic field analysis.Research limitations/implicationsThis paper considers an ideal condition for the AC arc. Non‐linearity of the arc during the melting, which leads to power quality disturbances, is not considered. In most prior researches on the electrical arc furnace, a non‐linear circuit model is usually used for calculation of power quality phenomena distributions. In this paper, the FEM is used instead of non‐linear circuits, and calculated voltage and current densities in the linear arc model. The FEM results directly depend on the physical properties considered for the arc.Originality/valueSteady‐state arc shapes, based on the Bowman model, are used to calculate and evaluate the geometry of the arc in a real and practical three‐phase AC arc furnace. A new approach to modeling AC arcs is developed, assuming that the instantaneous geometry of the AC arc at any time is constant and is similar to the geometry of a DC arc with the root mean square value of the current waveform of the AC arc. A time‐stepping 3D FEM is utilized to calculate the electromagnetic field in the AC arc as a function of time.

Data fusion system engineering

The paper reports on methods for the cost-effective development and integration of multi-sensor fusion technology. The methods presented extend the Project Correlation Data Fusion Engineering Guidelines with significant evolution. The key new insight is in formulating the system engineering process as a resource management problem; allowing the application of the Bowman's model of the duality between data fusion and resource management.

The Targowski & Bowman Model of Communication: Problems and Proposals for Adaptation

The Targowski & Bowman Model of Communication: Problems and Proposals for Adaptation

Resource constrained project crashing

The resource constrained project crashing problem is reviewed. Models for two specific cases are developed by extending traditional project scheduling models. The development of the model for the resource critical crashing case is based on the Pritsker, Watters, and Wolfe model [16]. The model developed for the activity duration crashing case is based on Bowman's model [2]. The paper concludes with several suggestions for future research.