Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
12
result(s) for
"Fish, J. (Jacob)"
Sort by:
Practical multiscaling
Practical Multiscaling covers fundamental modelling techniques aimed at bridging diverse temporal and spatial scales ranging from the atomic level to a full-scale product level. It focuses on practical multiscale methods that account for fine-scale (material) details but do not require their precise resolution. The text material evolved from over 20 years of teaching experience at Rensselaer and Columbia University, as well as from practical experience gained in the application of multiscale software.
This book comprehensively covers theory and implementation, providing a detailed exposition of the state-of-the-art multiscale theories and their insertion into conventional (single-scale) finite element code architecture. The robustness and design aspects of multiscale methods are also emphasised, which is accomplished via four building blocks: upscaling of information, systematic reduction of information, characterization of information utilizing experimental data, and material optimization. To ensure the reader gains hands-on experience, a companion website hosting a lite version of the multiscale design software (MDS-Lite) is available.
Key features:
* Combines fundamental theory and practical methods of multiscale modelling
* Covers the state-of-the-art multiscale theories and examines their practical usability in design
* Covers applications of multiscale methods
* Accompanied by a continuously updated website hosting the multiscale design software
* Illustrated with colour images
Practical Multiscaling is an ideal textbook for graduate students studying multiscale science and engineering. It is also a must-have reference for government laboratories, researchers and practitioners in civil, aerospace, pharmaceutical, electronics, and automotive industries, and commercial software vendors.
eBook
Mesoscopic and multiscale modelling in materials
The concept of multiscale modelling has emerged over the last few decades to describe procedures that seek to simulate continuum-scale behaviour using information gleaned from computational models of finer scales in the system, rather than resorting to empirical constitutive models. A large number of such methods have been developed, taking a range of approaches to bridging across multiple length and time scales. Here we introduce some of the key concepts of multiscale modelling and present a sampling of methods from across several categories of models, including techniques developed in recent years that integrate new fields such as machine learning and material design.
Multiscale modelling is a powerful tool to simulate materials behaviour, which has important features across multiple length and time scales. This Review provides an overview of multiscale computation methods and discusses their development for use in material design.
Journal Article
Psychiatric and Medical Profiles of Autistic Adults in the SPARK Cohort
This study examined lifetime medical and psychiatric morbidity reported by caregivers of 2917 autistic adults participating in the US research cohort SPARK. Participants were 78.4% male, 47.3% had intellectual disability, and 32.1% had persistent language impairments. Childhood language disorders (59.7%), speech/articulation problems (32.8%), sleep (39.4%) and eating problems (29.4%), motor delays (22.8%) and history of seizure (15.5%) were the most frequently reported clinical features. Over two thirds (67.2%) had been diagnosed with at least one psychiatric disorder (anxiety disorders: 41.1%; ADHD: 38.7%). Compared to verbally fluent participants, those with language impairments had lower frequencies of almost all psychiatric disorders. Female sex and older age were associated with higher medical and psychiatric morbidity.
Journal Article
Beliefs in vaccine as causes of autism among SPARK cohort caregivers
Fear of autism has led to a decline in childhood-immunization uptake and to a resurgence of preventable infectious diseases. Identifying characteristics of parents who believe in a causal role of vaccines for autism spectrum disorder (ASD) in their child may help targeting educational activities and improve adherence to the immunization schedule.
To compare caregivers of children with ASD who agree or disagree that vaccines play an etiological role in autism for 1) socio-demographics characteristics and 2) developmental and clinical profiles of their children.
Data from 16,525 participants with ASD under age 18 were obtained from SPARK, a national research cohort started in 2016. Caregivers completed questionnaires at registration that included questions on beliefs about the etiologic role of childhood immunizations and other factors in ASD. Data were available about family socio-demographic characteristics, first symptoms of autism, developmental regression, co-occurring psychiatric disorders, seizures, and current levels of functioning.
Participants with ASD were 80.4% male with a mean age of 8.1 years (SD = 4.1). Overall, 16.5% of caregivers endorsed immunizations as perceived causes of autism. Compared to caregivers who disagreed with vaccines as a cause for ASD, those who believed in vaccine causation came disproportionately from ethnic minority, less educated, and less wealthy backgrounds. More often their children had experienced developmental regression involving language and other skills, were diagnosed earlier, had lost skills during the second year of life, and had worse language, adaptive, and cognitive outcomes.
One in six caregivers who participate in a national research cohort believe that child immunizations could be a cause of autism in their child. Parent social background (non-White, less educated) and child developmental features (regression in second year, poorer language skills, and worse adaptive outcomes) index caregivers who are more likely to harbor these beliefs and could benefit from targeted educational activities.
Journal Article
Granulocytic Ehrlichiosis in the Laboratory Mouse
C3H mice that were inoculated with ehrlichiae isolated from a patient with human granulocytic ehrlichiosis (HGE) developed anemia and leukopenia, but by day 24, they returned to normal values. Granulocytic morulae were present in peripheral blood and spleen smears on days 5 and 10, and there was a reduction in morulae on day 17. Ehrlichiae were present in HL-60 cell cultures of blood and spleen from all mice at all intervals. Pathogenicity, but not infectivity, waned with mouse passage but could be resurrected by SCID mouse passage. Various methods were tested for their relative sensitivity in detecting infection: blood smears, HL-60 cell cultures, polymerase chain reaction (PCR) amplification of a 16S recombinant DNA target, and a mouse infectivity assay. All assays detected the HGE agent in blood during early infection, but PCR and the mouse infectivity assay were most sensitive during late infection. Xenodiagnosis demonstrated that mice remain persistently infected through 55 days.
Journal Article
Stabilized nonlocal model for dispersive wave propagation in heterogeneous media
In this paper, a general-purpose computational model for dispersive wave propagation in heterogeneous media is developed. The model is based on the higher-order homogenization with multiple spatial and temporal scales and the C0-continuous mixed finite element approximation of the resulting nonlocal equations of motion. The proposed nonlocal Hamilton principle leads to the stable discrete system of equations independent of the mesh size, unit cell domain and the excitation frequency. The method has been validated for plane harmonic analysis and for transient wave motion insemi-infinite domain with various microstructures.
Journal Article
A transonic small-disturbance model for the propagation of weak shock waves in heterogeneous gases
The interaction of weak shock waves with small heterogeneities in gaseous media
is studied. It is first shown that various linear theories proposed for this problem
lead to pathological breakdowns or singularities in the solution near the wavefront
and necessarily fail to describe this interaction. Then, a nonlinear small-disturbance
model is developed. The nonlinear theory is uniformly valid and accounts for the
competition between the near-sonic speed of the wavefront and the small variations of
vorticity and sound speed in the heterogeneous media. This model is an extension of
the transonic small-disturbance problem, with additional terms accounting for slight
variations in the media. The model is used to analyse the propagation of the sonic-boom
shock wave through the turbulent atmospheric boundary layer. It is found that,
in this instance, the nonlinear model accounts for the observed behaviour. Various
deterministic examples of interaction phenomena demonstrate good agreement with
available experimental data and explain the main observed phenomena in Crow (1969).
Journal Article
Investigation and identification of physical mechanism for enhanced thermal conductivity in nanofluids using molecular level modeling
Over the last decade a significant research effort has been committed to exploring the thermal transport properties of colloidal suspensions of nanosized solid particles (nanofluids). Initial experiments with Cu-water nanofluids measured up to a 40% increase in thermal conductivity for a mere 0.3% volume fraction of ∼10 nanometer (nm) diameter Cu particles. This increase is significantly larger than predicted by effective medium theory (EMT) of a composite material comprised of well dispersed particles. However, other experimental work on various compositions of nanoparticles and fluids has demonstrated thermal conductivity increases more in line with EMT. A number of possible origins for such behavior have been proposed, but a consensus has yet to emerge. More of the literature attempts to find correlations based on EMT that fit the experimental data rather than exploring the underlying mechanism. The likely candidate theories of liquid layering at the particle-fluid interface, Brownian motion induced heat transfer and particle aggregation are thoroughly explored in this thesis. We undertake a systematic investigation of these most likely mechanisms for enhanced thermal conductivity in nanofluids utilizing various analytical modeling techniques including equilibrium and non-equilibrium molecular dynamics (MD). We demonstrate that aggregation of nanoparticles is the most likely mechanism for enhanced thermal conductivity. We also include the effect of Kapitza interfacial resistance and aggregate shape on nanofluid thermal conductivity. Using our aggregate models, we investigate nanofluid viscosity. Nanoparticle clusters are shown to increase the nanofluid viscosity by up to 75% at 5% volume fraction. Overall the nanofluid exhibits shear thinning behavior.
Dissertation