Dynamic Load Measurement of Ballistic Gelatin Impact Using an Instrumented Tube

Bird strikes are a common problem for the aerospace industry and can cause serious damage to an aircraft. Ballistic gelatin is frequently used as a surrogate for actual bird carcasses in bird strike tests. Numerical simulations of these tests are used to supplement experimental data, therefore it is necessary to use numerical modeling techniques that can accurately capture the dynamic response of ballistic gelatin. An experimental technique is introduced to validate these modeling techniques. A ballistic gelatin projectile is fired into a strike plate attached to a 36 in. long sensor tube. Dynamic load is measured at two locations relative to the strike plate using strain gages configured in a full Wheatstone bridge. Data from these experiments are used to validate a gelatin constitutive model. Simulations of the apparatus are analyzed to investigate its performance

Adiabatic Heating of Austenitic Stainless Steels at Different Strain Rates

This work focuses on the effect of strain rate on the mechanical response and adiabatic heating of two austenitic stainless steels. Tensile tests were carried out over a wide range of strain rates from quasi-static to dynamic conditions, using a hydraulic load frame and a device that allowed testing at intermediate strain rates. The full-field strains of the deforming specimens were obtained with digital image correlation, while the full field temperatures were measured with infrared thermography. The image acquisition for the strain and temperature images was synchronized to calculate the Taylor–Quinney coefficient (β). The Taylor–Quinney coefficient of both materials is below 0.9 for all the investigated strain rates. The metastable AISI 301 steel undergoes an exothermic phase transformation from austenite to α’-martensite during the deformation, which results in a higher value of β at any given strain, compared to the value obtained for the more stable AISI 316 steel at the same strain rate. For the metastable 301 steel, the value of β with respect to strain depends strongly on the strain rate. At strain rate of 85 s−1, the β factor increases from 0.69 to 0.82 throughout uniform elongation. At strain rate of 10−1 s−1, however, β increases during uniform deformation from 0.71 to a maximum of 0.95 and then decreases to 0.91 at the start of necking.publishedVersionPeer reviewe

Interaction between behavioral inhibition and neural alcohol cue-reactivity in ADHD and alcohol use disorder

Rationale: Compared to the general population, adult Attention-Deficit-/Hyperactivity Disorder (ADHD) is more prevalent in patients with Alcohol Use Disorder (AUD). Impaired behavioral inhibition is a common characteristic in both ADHD and AUD. Relapse risk is increased in patients with AUD and comorbid, untreated ADHD and in AUD patients with increased neural cue-reactivity. Objectives: In this study, we examined the interaction between neural correlates of behavioral inhibition and alcohol cue-reactivity with a hybrid imaging task. Methods: Out of 69 adult study participants, we included n = 49 in our final analyses: Individuals had a diagnosis of either AUD (n = 13), ADHD (n = 14) or both (n = 5), or were healthy controls (HC; n = 17). The functional magnetic resonance imaging paradigm aimed to examine the combined effects of both an interference-inhibition task ('Simon-task') and an alcohol cue-reactivity task. Instead of segregating by diagnostic group, we pursued a dimensional approach in which we compared measures of AUD and ADHD severity, as well as the interaction of both, using multiple regression analyses. Results: The four groups did not differ on the behavioral level on either the inhibition task or the alcohol cue-reactivity task. However, brain activation in frontal control and reward-related regions during completion of the combined tasks were related to ADHD and AUD severity (symptom load). During presentation of both alcohol cues and the inhibition task, participants with higher AUD and ADHD symptom load exhibited greater BOLD (blood oxygen level dependent) responses in subcortical reward-related regions. Conclusions: Our findings support the hypothesis that ADHD additionally diminishes inhibition ability in individuals with AUD. This may increase relapse risk when confronted with alcohol cues. Further, it is crucial for patients with comorbid AUD and ADHD to take into account not only reduced cognitive control over behavioral inhibition but also simultaneously heightened alcohol cue-reactivity