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The phenomenon of drop-wall interaction plays a crucial role in a wide range of industrial applications. When liquid droplets come into contact with a high-temperature surface, it can lead to thermal shock due to rapid temperature fluctuations. This abrupt temperature change can generate thermal stress within the solid wall material. If the thermal stress exceeds the material's strength in that specific stress mode, it can result in material failure. Therefore, it is imperative to delve into the evolving temperature patterns on high-temperature surfaces to optimize material durability. This study focuses on investigating drop-wall interactions within the context of engine environments. To achieve this, the Smoothed Particle Hydrodynamics (SPH) method is employed to simulate the impact of fuel droplets on a silicon nitride wall. The goal is to understand the heat transfer mechanisms, thermal penetration depths, and temperature distributions within the heated wall.

There is a growing interest in ammonia as a potential carbon-free fuel due to the current trend of decarbonization in ground transportation. Benefits of ammonia as a fuel include its high volumetric energy density, ease of storage and transportation, and mature manufacturing infrastructure. On the other hand, ammonia suffers from a low flame speed, long ignition delay times and NOx formation. In this work, a computational investigation of ammonia and hydrogen blends in a 0-D homogeneous charge compression ignition reactor is conducted using different blends under a range of engine-relevant conditions. Iso-contours of the crank angle corresponding to 50% of total heat release (CA50) are developed to assess the reactivity of the different blends under different engine speeds and equivalence ratios. The results show that ammonia requires a high inlet temperature to achieve a CA50 close to top dead center (TDC).

Understanding the fundamental details of drop/wall interactions is important to improving engine performance. Most of the drop-wall interactions studies are based on the impact of a single drop on the wall. To accurately mimic and model the real engine conditions, it is necessary to characterize spray/wall interactions with different impingement frequencies at a wide range of wall temperatures. In this study, a numerical method, based on Smoothed Particle Hydrodynamics (SPH), is used to simulate consecutive droplet impacts on a heated wall both below and above the Leidenfrost temperature. Impact regimes are identified for various impact conditions by analyzing the time evolution of the post-impingement process of n-heptane drops at different impingement frequencies and wall surface temperatures. For wall temperature below the Leidenfrost temperature, the recoiled film does not leave the surface.

A CAE-based optimization method is developed for Lube Oil Consumption (LOC) analysis of the piston-ring system. With accurate thermodynamic boundary conditions from 1D engine combustion simulation, piston motion, dynamics of piston ring, and characteristics of oil consumption are simulated using AVL Piston&Ring. The model is validated by comparing with available test data. Good match is achieved. The model is then applied to a diesel engine. The root cause of excessive LOC of the engine has been identified through CAE. The improved understanding has been applied to optimize the piston and piston ring. Engine dyno test, 1200-hour engine durability test, and 45000-kilometer vehicle test have been conducted to validate the optimized design. The experiment results are in good agreement with CAE predictions, and the oil consumption has been improved over the original design.

Experimental studies of soot particles showed that the intensity ratio of amorphous and graphite layers measured by Raman spectroscopy correlates to soot oxidation reactivities, which is very important for regeneration of the diesel particulate filters and gasoline particulate filters. This physical mechanism is absent in all soot models. In the present paper, a novel two-layer soot model was proposed that considers the amorphous and graphite layers in the soot particles. The soot model considers soot inception, soot surface growth, soot oxidation by O2 and OH, and soot coagulation. It is assumed that amorphous-type soot forms from fullerene. No soot coagulation is considered in the model between the amorphous- and graphitic-types of soot. Benzene is taken as the soot precursor, which is formed from acetylene. The model was implemented into a commercial CFD software CONVERGE using user defined functions. A diesel engine case was simulated.

Machine learning methods, such as decision trees and deep neural networks, are becoming increasingly important and useful for data analysis in various scientific fields including dynamics and control, signal processing, pattern recognition, fluid mechanics, and chemical synthesis, etc. For future engine design and performance optimization, there is an urgent need for a robust predictive model which could capture the major combustion properties such as autoignition and flame propagation of multicomponent fuels under a wide range of engine operating conditions, without massive experimental measurement or computational efforts. It will be shown that these long-held limitations and challenges related to complex fuel combustion and engine research could be readily solved by implementing machine learning methods.

The application of Computational Fluid Dynamics (CFD) for three-dimensional (3D) combustion analysis coupled with detailed chemistry in engine development is hindered by its expensive computational cost. Chemistry computation may occupy as much as 90% of the total computational cost. In the present paper, a new two-step iso-octane combustion model was developed for spark-ignited (SI) engine to maximize computational efficiency while maintaining acceptable accuracy. Starting from the model constants of an existing global combustion model, the new model was developed using an approach based on sensitivity analysis to approximate the results of a reference skeletal mechanism. The present model involves only five species and two reactions and utilizes only one uniform set of model constants. The validation of the new model was performed using shock tube and real SI engine cases.

In recent years, study on the ride comfort of vehicles has attracted wide attention. The vibration caused by the road is transmitted to the human body through the tire, suspension, vehicle body, and the seat. Since the human body is in contact with the seat and the vibration is transmitted directly to the human body through the seat, the seat pan angle plays an important role on the vibration response of the human body. Previous studies have explored the effects of different backrest designs on human vibration response, but ignored the effects of different seat pan angles. Therefore, this paper will use a human biodynamic model combined with a 6-DOF seat model to study the effect of seat pan angles and feet-floor interaction on human vibration response. Three cases are proposed: Case 1 has a seat pan angle 8°, Case 2 has a seat pan angle 13°, and Case 3 has a seat pan angle 17°.

Flame speed data reported in most literature are acquired in conventional apparatus such as the spherical combustion bomb and counterflow burner, and are limited to atmospheric pressure and ambient or slightly elevated unburnt temperatures. As such, these data bear little relevance to internal combustion engines and gas turbines, which operate under typical pressures of 10-50 bar and unburnt temperature up to 900K or higher. These elevated temperatures and pressures not only modify dominant flame chemistry, but more importantly, they inevitably facilitate pre-ignition reactions and hence can change the upstream thermodynamic and chemical conditions of a regular hot flame leading to modified flame properties. This study focuses on how auto-ignition chemistry affects flame propagation, especially in the negative-temperature coefficient (NTC) regime, where dimethyl ether (DME), n-heptane and iso-octane are chosen for study as typical fuels exhibiting low temperature chemistry (LTC).

Pressure ringing phenomena in internal combustion engine are often observed in cylinder pressure measurement, which may be due to combustion dynamics, pressure oscillation inside the combustion chamber and/or inside a drilled probe hole for cylinder pressure sensor installation. In the present study, combustion process in a production DI diesel engine instrumented with pressure sensors in the cylinder head was analyzed using 3D combustion CFD simulation. Three combustion models (the CTC model with the Shell autoignition model, the Sage model with detailed chemistry, and the ECFM-3Z model) and three reaction mechanisms (the Shell autoignition model, the Chalmers reduced n-heptane mechanism, and the IFP PRF mechanism) were employed to validate their capability in capturing pressure ringing phenomena. Grid size within the drilled hole and speed of sound CFL number were varied to evaluate the effects on pressure ringing prediction.

Vehicle tire performance is an important consideration for vehicle handling, stability, mobility, and ride comfort as well as durability. Significant efforts have been dedicated to tire modeling in the past, but there is still room to improve its accuracy. In this study, a detailed in-plane flexible ring tire model is proposed, where the tire belt is discretized, and each discrete belt segment is considered as a rigid body attached to a number of parallel tread blocks. The mass of each belt segment is accumulated at its geometric center. To test the proposed in-plane tire model, a full-vehicle model is integrated with the tire model for simulation under a special driving scenario: acceleration from rest for a few seconds, then deceleration for a few seconds on a flat-level road, and finally constant velocity on a rough road. The simulation results indicate that the tire model is able to generate tire/road contact patch forces that yield reasonable vehicle dynamic responses.

A tire may be one of the most critical and complex components in vehicle dynamics and road loads analyses because it serves as the only interface between the road surface and the vehicle. Extensive research and development activities about vehicle dynamics and tire models have been published in the past decades, but it is still not clear about the applications and parameter identification associated with all of these tire models. In this literature review study, various published tire models used for vehicle dynamics and road loads analyses are compared in terms of their modeling approaches, applications and parameters identification process and methodologies. It is hoped that the summary of this literature review work can help clarify and guide the future research and development direction about tire modeling.

In vehicle driving environment, the driver is subjected to the vibrations in horizontal, vertical, and fore-aft directions. The human body is very much sensitive to whole body vibration and this vibration transmission to the body depends upon various factors including road irregularities, vehicle suspension, vehicle dynamics, tires, seat design and the human body's properties. The seat design plays a vital role in the vibration isolation as it is directly in contact with human body. Vibration isolation properties of a seat depend upon its dynamic parameters which include spring stiffness and damping of seat suspension and cushion. In this paper, an optimization-based method is used to determine the optimal seat dynamic parameters for seat suspension, and cushion based on minimizing occupant's body fatigue (occupant body absorbed power). A 14-degree of freedom (DOF) multibody biodynamic human model in 2D is selected from literature to assess three types of seat arrangements.

Digital human modeling and posture prediction can only be used as a design tool if the predicted postures are realistic. To date, the most realistic postures have been realized by simultaneously optimizing human performance measures (HPMs). These HPMs currently consist of joint discomfort, delta potential energy, and visual displacement. However these HPMs only consider the kinematics of human posture. Dynamic aspects of human posture such as external loads and mass of limbs have not yet been considered in conjunction with the current HPMs. This paper gives the formulation for a new human performance measure combination including the use of joint torque to account for the dynamics of human posture. Postures are then predicted using multi-objective optimization (MOO) techniques to optimize the combination of the new HPM and the current. The predicted postures are then compared with the benchmark postures which are those obtained from using the current HPMs only.

Biological pre-treatment of early planetary/lunar base wastewater has been extensively studied because of its predicted ability to offer equivalent system mass (ESM) savings for long term space habitation. Numerous biological systems and reactor types have been developed and tested for treatment of the generally unique waste streams associated with space exploration. In general, all systems have been designed to reduce organic carbon (OC) and convert organic nitrogen (ON) to nitrate and/or nitrite (NOx -). Some systems have also included removal of the oxidized N in order to reduce overall oxygen consumption and produce additional N2 gas for cabin use. Removal of organic carbon will generally reduce biofouling as well as reduce energy and consumable cost for physiochemical processors.

Comfort assessment of respirator fit plays an important role in the respirator design process and standard development. To reduce the cost and design time of respirators, the design, fit, and evaluation process can be performed in a virtual environment. Literature shows that respirator-induced discomfort relates to stress, area, and region of the face covered. In this work, we investigate the relationship between the strap tensions and the stress and deformation distribution on the interface between the respirator and the headform. This is the first step towards a comprehensive understanding of the contribution of contact stress to the mathematical comfort fit model. The 3D digital models for respirators and headforms have been developed based on 3D scanning point-cloud using a Cyberware® 3D digitizer. Five digital headform models have been generated: small, medium, large, long and short.

Microbial control in closed environmental systems, such as those of spacecraft or proposed base missions is typically limited to disinfection in the potable water system by a strong chemical agent such as iodine or chlorine. However, biofilm growth in the environmental system tubing threatens both the sterility of the potable water distribution as well as operational problems with wastewater systems. In terrestrial systems, biofilm has been recognized for its difficulty to control and eliminate as well as resulting operational problems. In order to maintain a potable water source for crew members as well as preventing operational problems in non-sterile systems, biofilm needs to be considered during system design. While biofilm controls can limit biofilm buildup, they are typically disruptive and cannot completely eliminate biofilm. Selenium coatings have shown to prevent initial biofilm attachment as well as limit attached growth on a variety of materials.

A modified membrane-aerated biofilm reactor (mMABR) was constructed by incorporating two distinct biofilm immobilization media: gas-permeable hollow fiber membranes and high surface area inert bio-media. In order to evaluate the mMABR for space flight applications, a synthetic ersatz early planetary base (EPB) waste stream was supplied as influent to the reactor, and a liquid loading study was conducted at three influent flow rates. On average, percent carbon removal ranged from 90.7% to 93.1% with volumetric conversion rates ranging from 25 ± 3.3 g / m3 d and 95 ± 13.4 g / m3 d. Simultaneous nitrification/denitrification (SND) was achieved in a single reactor. As the liquid loading rate increased from 0.15 mL/min to 0.45 mL/min, the volumetric denitrification rates elevated from 27 ± 3.3 g / m3 d to 65 ± 5.2 g / m3 d. Additionally, it was found that nitrification and denitrification were linearly related with respect to both percent efficiency and volumetric reaction rates.

Hollow fiber membrane reactors (HFMBRs) may be used for biological wastewater treatment, and may be integrated with NASA's current research developments. The goal of this paper is to (a) evaluate the effect of mass transfer and hydrodynamics in a microporous HFMBR and (b) appropriateness of HFMBRs for use in space applications. Even though bubble-less aeration was not achieved by the use of microporous membranes, mass transfer within the HFMBR was found to increase after biofilm formation. Conversely, convective flow dominated transport within the system. Despite the high treatment efficiency obtained by the HFMBR, due to the bioreactor size, configuration and membrane spacing within the HFMBR, the bioreactor was not a suitable option for application under microgravity conditions. Even though developing a system with more favorable system hydrodynamics would aid in treatment efficiency, the use of a microporous HFMBR is not a recommended option to meet NASA's needs.

The feasibility of a long-term space mission is partially reliant upon the ability to effectively recycle wastewater. Merged biological and physiochemical processes (integrated water recovery systems (IWRS)) are capable of producing potable water at lower equivalent system mass (ESM) than treatment systems composed of only physiochemical processes. Reducing the ESM of the water recycling units can increase the practicality of extended space missions by decreasing payload weight. In order to lower the ESM of the biological pre-treatment component, a single-stage biological reactor capable of simultaneous carbon and nitrogen removal was created by modifying the membrane-aerated biofilm reactor (MABR) design. Studies were performed in order to evaluate the water quality performance of this reactor.