Prediction of blood back spatter from a gunshot in bloodstain pattern analysis

A theoretical model for predicting and interpreting blood-spatter patterns resulting from a gunshot wound is proposed. The physical process generating a backward spatter of blood is linked to the Rayleigh-Taylor instability of blood accelerated toward the surrounding air, allowing the determination of the initial distribution of drop sizes and velocities. Then the motion of many drops in air is considered with governing equations accounting for gravity and air drag. Based on these equations, a numerical solution is obtained. It predicts the atomization process, the trajectories of the back-spatter drops of blood from the wound to the ground, the impact angle, and the impact Weber number on the ground, as well as the distribution and location of bloodstains and their shape and sizes. A parametric study is undertaken to predict patterns of backward blood spatter under realistic conditions corresponding to the experiments conducted in the present work. The results of the model are compared to the experimental data on back spatter generated by a gunshot impacting a blood-impregnated sponge

Hydrodynamics of back spatter by blunt bullet gunshot with a link to bloodstain pattern analysis

A theoretical model describing the blood spatter pattern resulting from a blunt bullet gunshot is proposed. The predictions are compared to experimental data acquired in the present work. This hydrodynamic problem belongs to the class of the impact hydrodynamics with the pressure impulse generating the blood flow. At the free surface, the latter is directed outwards and accelerated toward the surrounding air. As a result, the Rayleigh-Taylor instability of the flow of blood occurs, which is responsible for the formation of blood drops of different sizes and initial velocities. Thus, the initial diameter, velocity, and acceleration of the atomized blood drops can be determined. Then, the equations of motion are solved, describing drop trajectories in air accounting for gravity, and air drag. Also considered are the drop-drop interactions through air, which diminish air drag on the subsequent drops. Accordingly, deposition of two-phase (blood-drop and air) jets on a vertical cardstock sheet located between the shooter and the target (and perforated by the bullet) is predicted and compared with experimental data. The experimental data were acquired with a porous polyurethane foam sheet target impregnated with swine blood, and the blood drops were collected on a vertical cardstock sheet which was perforated by the blunt bullet. The highly porous target possesses a low hydraulic resistance and therefore resembles a pool of blood shot by a blunt bullet normally to its free surface. The back spatter pattern was predicted numerically and compared to the experimental data for the number of drops, their area, the total stain area, and the final impact angle as functions of radial location from the bullet hole in the cardstock sheet (the collection screen). Comparisons of the predicted results with the experimental data revealed satisfactory agreement. The predictions also allow one to find the impact Weber number on the collection screen, which is necessary to predict stain shapes and sizes

Control and ultrasonic actuation of a gas-liquid interface in a microfluidic chip

This article describes the design and manufacturing of a microfluidic chip, allowing for the actuation of a gas-liquid interface and of the neighboring fluid. A first way to control the interface motion is to apply a pressure difference across it. In this case, the efficiency of three different micro-geometries at anchoring the interface is compared. Also, the critical pressures needed to move the interface are measured and compared to theoretical result. A second way to control the interface motion is by ultrasonic excitation. When the excitation is weak, the interface exhibits traveling waves, which follow a dispersion equation. At stronger ultrasonic levels, standing waves appear on the interface, with frequencies that are half integer multiple of the excitation frequency. An associated microstreaming flow field observed in the vicinity of the interface is characterized. The meniscus and associated streaming flow have the potential to transport particles and mix reagents

Pattern formation during the evaporation of a colloidal nanoliter drop: a numerical and experimental study

An efficient way to precisely pattern particles on solid surfaces is to dispense and evaporate colloidal drops, as for bioassays. The dried deposits often exhibit complex structures exemplified by the coffee ring pattern, where most particles have accumulated at the periphery of the deposit. In this work, the formation of deposits during the drying of nanoliter colloidal drops on a flat substrate is investigated numerically and experimentally. A finite-element numerical model is developed that solves the Navier-Stokes, heat and mass transport equations in a Lagrangian framework. The diffusion of vapor in the atmosphere is solved numerically, providing an exact boundary condition for the evaporative flux at the droplet-air interface. Laplace stresses and thermal Marangoni stresses are accounted for. The particle concentration is tracked by solving a continuum advection-diffusion equation. Wetting line motion and the interaction of the free surface of the drop with the growing deposit are modeled based on criteria on wetting angles. Numerical results for evaporation times and flow field are in very good agreement with published experimental and theoretical results. We also performed transient visualization experiments of water and isopropanol drops loaded with polystyrene microsphere evaporating on respectively glass and polydimethylsiloxane substrates. Measured evaporation times, deposit shape and sizes, and flow fields are in very good agreement with the numerical results. Different flow patterns caused by the competition of Marangoni loops and radial flow are shown to determine the deposit shape to be either a ring-like pattern or a homogeneous bump

Effective velocity for transport in heterogeneous compressible flows with mean drift

Solving transport equations in heterogeneous flows might give rise to scale dependent transport behavior with effective large scale transport parameters differing from those found on smaller scales. For incompressible velocity fields, homogenization methods have proven to be powerful in describing the effective transport parameters. In this paper, we aim at studying the effective drift of transport problems in heterogeneous compressible flows. Such a study was done by Vergassola and Avellaneda in Physica D 106, 148 (1997). There, it was shown that for static compressible flow without mean drift, impacts on the large scale drift do not occur. We will first discuss the impact of a mean drift and show that static compressible flow with mean drift can produce a heterogeneity driven large scale drift (or ballistic transport). For the case of Gaussian stationary random processes, we derive explicit results for the large scale drift. Moreover, we show that the large scale or effective drift depends on the small scale diffusion coefficients and thus on the molecular weights of the particles. This study could be applied to weight-based particle separation. Numerical simulations are presented to illustrate these phenomena. © 2008 American Institute of Physics

What we talk about when we talk about uncertainty. Toward a unified, data-driven framework for uncertainty characterization in hydrogeology

In this manuscript, we compare and discuss different frameworks for hydrogeological uncertainty analysis. Since uncertainty is a property of knowledge, we base this comparison on purely epistemological concepts. In a detailed comparison between different candidates, we make the case for Bayesianism, i.e., the framework of reasoning about uncertainty using probability theory. We motivate the use of Bayesian tools, shortly explain the properties of Bayesian inference, prediction and decision and identify the most pressing current challenges of this framework. In hydrogeology, these challenges are the derivation of prior distributions for the parametric uncertainty, typically hydraulic conductivity values, as well as the most relevant paradigm for generating subsurface structures for assessing the structural uncertainty. We present the most commonly used paradigms and give detailed advice on two specific paradigms; Gaussian multivariate random fields as well as multiple-point statistics, both of which have benefits and drawbacks. Without settling for either of these paradigms, we identify the lack of open-access data repositories as the most pressing current impediment for the advancement of data-driven uncertainty analysis. We detail the shortcomings of the current situation and describe a number of steps which could foster the application of both the Gaussian as well as the multiple-point paradigm. We close the manuscript with a call for a community-wide initiative to create this necessary support