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Prediction and Control of In-Cylinder Processes in Heavy-Duty Engines Using Alternative Fuels
No full textThis Ph.D. thesis focuses on advancing diagnostic techniques and control-oriented models to enhance the efficiency and performance of internal combustion (IC) engines, particularly heavy-duty engines utilizing alternative fuels. The research endeavors to contribute to the field of model-based control of engines through the development and implementation of innovative methodologies. The primary emphasis is on the development of diagnostic methods, control-oriented models and advanced control strategies for compression ignition engines using alternative fuels. The first key topic explores the determination of the Most Representative Cycle for Combustion Phasing Estimation based on cylinder pressure measurements. The method developed extracts crucial information from experimental data obtained from four distinct engines: the heavy-duty single-cylinder GCI engine, the light-duty multi-cylinder diesel engine, a CFR engine, and a single-cylinder light-duty Spark Ignition (SI) engine. This work lays the foundation for precise combustion phasing estimation, a critical parameter for engine control. The second major contribution involves the development of control-oriented models for Variable Geometry Turbochargers (VGT) and inter-coolers. Two models are established: a data-driven turbocharger model and an empirical inter-cooler model. These models are meticulously calibrated and validated using experimental data from a multi-cylinder light-duty diesel engine, providing valuable insights into the behavior of these components under varying conditions. The outcomes contribute to facilitate predictive control of engine air systems. The third core aspect of the thesis revolves around Model Predictive Control of Combustion Phasing in heavy-duty compression-ignition engines utilizing alternative fuels. A combustion phasing and engine load model is derived from experimental data and incorporated into an MPC framework. The MPC strategy is subsequently tested in the heavy-duty GCI test cell and compared against a conventional Proportional-Integral-Derivative (PID) control strategy. The results showcase the effectiveness of the MPC approach in achieving precise control of combustion phasing, demonstrating its potential for optimizing engine performance.
In summary, this Ph.D. thesis contributes significantly to the field of engine controls by advancing diagnostic techniques, control-oriented models, and implementing a cutting-edge MPC-based control strategy for compression ignition engines using alternative fuels. The research findings not only enhance the understanding of in-cylinder processes but also pave the way for more efficient and sustainable heavy-duty engines using alternative fuels
Agency and Pathway Thinking as Mediators of The Relationship Between Caregiver Burden And Life Satisfaction Among Family Caregivers Of People With Parkinson’s Disease: An Application Of Snyder’s Hope Theory
No full textIn the United States, there are 47.9 million caregivers providing care to family members with disabilities. Those providing care to someone who has Parkinson’s Disease (PD), a complex degenerative movement disorder, may have a unique caregiving experience, given that disease-related factors (e.g. motor and non-motor symptoms) can contribute to worsening caregiver burden and life satisfactions (LS). PD has an increasing incidence of 90,000 new cases per year, likely resulting in an increased need for caregivers. Caregiving research frequently focuses on the mediators between caregiver burden and LS including social support, coping skills, and appraisals. Research that has specifically focused on caregivers of people with PD (Pw/PD) is significantly limited. Hope is a “positive motivational characteristic comprised of agency and pathways thinking that can help facilitate drive towards one’s goal while also serving as a buffer against negative events” (Snyder et al.,1991). The goal of this study is to understand Snyder’s hope theory as it relates to caregiver burden and LS for caregivers of Pw/PD. Specifically, we hypothesized that (a) caregiver burden will be negatively correlated with agency thinking, pathways thinking, and LS among caregivers of Pw/PD. In addition, pathways thinking, and agency thinking will be positively associated with LS, and (b) agency thinking, and pathways thinking will mediate the relationship between caregiver burden and LS among caregivers of Pw/PD. The study sample consisted of 249 caregivers of Pw/PD who completed an online anonymous questionnaire. Correlations between agency and pathways thinking, LS, caregiver burden, and sociodemographic factors were evaluated. A parallel mediation analysis was run to evaluate the mediating roles of pathways and agency thinking in the relationship between caregiver burden and LS. Results indicated that LS was significantly and negatively correlated with caregiver burden. LS was significantly and positively correlated with both pathways and agency thinking. Pathways thinking had no indirect effect on the relationship of caregiver burden on LS. Agency thinking had a negative, indirect effect on the relationship suggesting that agency thinking partially mediated the relationship between caregiver burden and LS. Clinical implications and future directions are discussed
Goal Orientation, Personality, and Time and Their Influences on Profiles of Self-Regulated Learning
No full textThis exploratory study investigates profiles of self-regulated learning (SRL) and expands on a gap in previous research. Previously found profiles were summarized, replicated, and differences among profiles in academic outcomes, personality, and goal orientation were examined. Additionally, these relationships were examined longitudinally to investigate whether personality or goal orientation predicted stability of profile membership. Four profiles were found using latent profile analysis in a participant pool of 270 undergraduate and graduate students: a very high SRL profile, a high SRL profile, an unmotivated but strategic SRL profile, and a low SRL profile. One-way ANOVA revealed grades did not differ significantly among profiles. Regression analysis found LGO, openness to experience, conscientiousness, and extraversion were significant predictors of SRL profile. Latent transition analysis was used for longitudinal analysis. Over time, participants were more likely to move from profiles utilizing more SRL to profiles of lower SRL. Generally, openness to experience, extraversion, agreeableness, and neuroticism predicted change more than stability, while PPGO predicted stability more than chang
Rapid Ex Vivo Detection of Cancer in Excised Lymph Nodes: Development of a Tissue Model and Initial Results
No full textThere are millions of new head and neck cancers diagnosed each year, and it is one of the most aggressive cancers. The typical first line of therapy for head and neck cancers is surgery; however, if the cancer has spread (metastasized) from the primary tumor, more advanced surgery and/or adjuvant therapy (chemotherapy and or radiation therapy) can be indicated. Clinically, metastasis is diagnosed by surgically removing one or more lymph nodes draining the primary tumor during the primary tumor resection. Each lymph node located and removed adds to the morbidity of the procedure, so many clinics are moving toward a “sentinel” lymph node biopsy strategy, where only the first lymph node draining the tumor is removed and sent to pathology. Assessment of the node for cancer can take up to a week. If this lymph node is found to have cancer, the patient is then asked to return for a secondary surgery where a complete neck dissection is carried out (removal of all the lymph nodes in the side of the neck ipsilateral to the tumor). This delay in diagnosis is stressful on patients, adds health care costs, and considering the invasiveness of some primary tumor resections, some patients opt not to return for callback surgeries even though it would improve their chances of survival. This thesis presents efforts to test the ability for a fluorescence molecular imaging system called “agent-dependent enhanced photon tomography” (ADEPT) to be able to detect cancer in an excised sentinel lymph node while the patient is still on the operating table. This would allow a significant reduction in the number of patients requiring callback surgeries. Specifically, this thesis explores (in chapter 1) the development of a porcine lymph node fresh tissue model using implanted human cancer spheroids to act as realistic models of a freshly excised sentinel lymph node; (in chapter 2) the advancement of this tissue model to include a range of cancer burden levels and cancer cells strains; (and in chapter 3) a first demonstration of the ADEPT system applied to these realistic tissue models to detect clinically relevant levels of cancer. The ADEPT is a prototype designed specifically for the purpose of being faster in terms of processing and eliminates the need for patient to come back surgeries. We were able to validate ADEPT by incorporating a metastatic model mimicking a human lymph node and verifying the presence of cancer tumor that was manually injected into the lymph node followed by infusion of imaging agents
Resolvent Analysis of Turbulent Flow over Compliant Surfaces: Optimization Methods and Stability Considerations.
No full textThis thesis delves into the manipulation of turbulence properties through innovative compliant surface designs. Turbulence, known for its unpredictable fluid movements, presents substantial challenges across engineering disciplines, particularly in optimizing system efficiency and minimizing energy losses. This research explores the potential of compliant surfaces to control and mitigate the adverse effects of turbulent flow, thereby enhancing the performance and reliability of engineering systems.Employing the resolvent analysis method, this work investigates the interaction between turbulent flows and surfaces capable of dynamic adaptation. The study evaluates the impact of these surfaces on turbulence suppression through the application of both space-dependent and independent compliance models, where the compliance model is characterised by an admittance, which represents the relationship between the instantaneous surface pressure and surface velocity. This approach allows for a nuanced understanding of how different surface properties can influence the behavior of turbulent flows.A significant contribution of this thesis is the comprehensive stability analysis conducted to assess the implications of compliant surfaces on the linear stability of the dynamical system. By examining the eigenvalues of the mean-linearized system, the research identifies the conditions under which compliant surfaces may induce or mitigate instabilities within turbulent flows. This analysis is pivotal in developing compliant surface designs that not only reduce turbulence-induced energy losses but also ensure the stability of the flow, a critical consideration for practical engineering applications.The findings of this thesis offer valuable insights into the role of surface compliance in turbulence control, paving the way for further research and the development of advanced engineering solutions. Through a detailed investigation of the interactions between compliant surfaces and turbulent flows, this work contributes to the broader field of fluid dynamics and underscores the potential of innovative surface designs in achieving more efficient and sustainable engineering systems
Exploring the role of perceived trustworthiness on leader humility's effectiveness
No full textOver the last decade, several studies have uncovered the value of leader humility; however, these findings fail to consider the contextual factors that may alter when and how humility plays a role. The current study looks to bridge this gap, by exploring how the effectiveness of perceived leader humility on follower outcomes (i.e., state learning goal orientation, feedback seeking behaviors, and employee engagement) is contingent upon follower perceptions of the leader’s trustworthiness. Data was collected from 160 leader-follower dyads across a variety of industries, using a cross-sectional design. Results from the study reinforced earlier findings that leader humility is often associated with positive follower outcomes such as seeking more feedback and reporting a higher learning goal orientation; however, these results were contingent upon how trustworthy they perceived the leader to be. Additionally, the study found evidence that perceptions of leader trustworthiness were related to group-based differences (e.g., age, gender). Together, these findings serve as a reminder that studying leader behaviors in isolation often risks simplifying the complex reality most leader’s face when trying to implement leader behaviors and skills
Extremal and Enumerative Problems on DP-Coloring of Graphs
No full textGraph coloring is the mathematical model for studying problems related to conflict-free allocation of resources. DP-coloring (also known as correspondence coloring) of graphs is a vast generalization of classic graph coloring, and many more concepts of colorings studied in the past 150+ years.
We study problems in DP-coloring of graphs that combine questions and ideas from extremal, structural, probabilistic, and enumerative aspects of graph coloring. In particular, we study (i) DP-coloring Cartesian products of graphs using the DP-color function, the DP coloring counterpart of the Chromatic polynomial, and robust criticality, a new notion of graph criticality; (ii) Shameful conjecture on the mean number of colors used in a graph coloring, in the context of list coloring and DP-coloring; and (iii) asymptotic bounds on the difference between the chromatic polynomial and the DP color function, as well as the difference between the dual DP color function and the chromatic polynomial, in terms of the cycle structure of a graph. These results respectively give an upper bound and a lower bound on the chromatic polynomial in terms of DP colorings of a graph
Retrospective Quantitative T1 Imaging to Examine Characteristics of Multiple Sclerosis Lesions
No full textQuantitative MRI plays an essential role in assessing tissue abnormality and diseaseprogression in multiple sclerosis (MS). Specifically, T1 relaxometry is gaining popularity
as elevated T1 values have been shown to correlate with increased inflammation,
demyelination, and gliosis. The predominant issue is that relaxometry requires parametric
mapping through advanced imaging techniques not commonly included in standard clinical
protocols. This leaves an information gap in large clinical datasets from which quantitative
mapping could have been performed.
We introduce T1-REQUIRE, a retrospective T1 mapping method that approximates
T1 values from a single T1-weighted MR image. This method has already been shown to
be accurate within 10% of a clinically available reference standard in healthy controls but
will be further validated in MS cohorts. We also further aim to determine T1-REQUIRE’s
statistical significance as a unique biomarker for the assessment of MS lesions as they
relate to clinical disability and disease burden.
A 14-subject comparison between T1-REQUIRE maps derived from 3D T1
weighted turbo field echoes (3D T1w TFE) and an inversion-recovery fast field echo (IRFFE) revealed a whole-brain voxel-wise Pearson’s correlation of r = 0.89 (p < 0.001) and
mean bias of 3.99%. In MS white matter lesions, r = 0.81, R2 = 0.65 (p < 0.001, N = 159),
bias = 10.07%, and in normal appearing white matter (NAWM), r = 0.82, R
2 = 0.67 (p <
0.001), bias = 9.48%.
Mean lesional T1-REQUIRE and MTR correlated significantly (r = -0.68, p <
0.001, N = 587) similar to previously published literature. Median lesional MTR correlated
significantly with EDSS (rho = -0.34, p = 0.037), and lesional T1-REQUIRE exhibited
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significant correlations with global brain tissue atrophy as measured by brain parenchymal
fraction (BPF) (r = -0.41, p = 0.010, N = 38). Multivariate linear regressions between T1-
REQUIRE NAWM provided meaningful statistical relationships with EDSS (β = 0.03, p
= 0.027, N = 38), as well as did mean MTR values in the Thalamus (β = -0.27, p = 0.037,
N = 38).
A new spoiled gradient echo variation of T1-REQUIRE was assessed as a proof of concept
in a small 5-subject MS cohort compared with IR-FFE T1 maps, with a whole brain voxel-wise
correlation of r = 0.88, R2 = 0.77 (p < 0.001), and Bias = 0.19%. Lesional T1 comparisons
reached a correlation of r = 0.75, R2 = 0.56 (p < 0.001, N = 42), and Bias = 10.81%.
The significance of these findings means that there is the potential to provide
supplementary quantitative information in clinical datasets where quantitative protocols
were not implemented. Large MS data repositories previously only containing structural
T1 weighted images now may be used in big data relaxometric studies with the potential
to lead to new findings in newly uncovered datasets. Furthermore, T1-REQUIRE has the
potential for immediate use in clinics where standard T1 mapping sequences aren’t able to
be readily implemented
Cultivating Narrative Change in Collective Sensemaking
No full textThe complexity of social and ecological crises and the need for collective action to tackle them brought forth collective inquiry as an essential capacity for societies to combine their knowledge and creativity, navigate complexity, and respond with adaptive solutions. However, current approaches to sensemaking often remain anchored in the same mindsets and worldviews that underpin these crises, constraining their ability to account for the fundamental shifts needed. This research addresses this gap by exploring how collective inquiry, when framed as a narrative practice, can open space for alternative perspectives and pathways in systems transformation. This study positions narratives as dynamic meaning systems that shape how groups interpret issues, determine relevance, and envision new possibilities. The dissertation is structured as three studies, situated in the context of food systems, each exploring ways to engage and mobilize these meaning systems across different contexts and scales of collective inquiry. A central contribution of this research is the framework of narrative infrastructures—the social and material contexts through which narratives of change are constructed, circulated, and sustained within systems change efforts. This framework supports designers in navigating and shaping the spaces where narratives are articulated, contested, and maintained, to foster more critical, pluralistic, and transformative approaches to collective inquiry. Ultimately, this work enhances design’s capacity to foster the shifts in mindsets through which societies envision their collective futures, using its narrative agency to disrupt harmful paradigms and open space for radical possibilities in the making
Automated techniques for enhancing developer productivity on disaggregated software stacks
No full textThe rapid advances in specialized hardware, capabilities including FPGAs, TPUs,microsecond network interconnects, RDMA, GPUs, and other technologies have posed
significant challenges for the traditional monolithic client/server model in efficiently man-
aging and scaling resources, both within industry and HPC systems. This challenge has in-
stigated the emergence of a new paradigm known as resource disaggregation, which tackles
the limitations of the monolithic client-server paradigm by enabling independent scaling of
components such as compute, memory, and storage. The disaggregation of resources can
be managed entirely through hardware or software solutions. Resource disaggregation en-
hances resource utilization by fine grained scheduling of hardware resources to support
dynamic workloads efficiently and empowers data centers to effectively address varying
computational demands, optimize performance, and curtail operational costs, marking a
pivotal evolution in modern computational infrastructure.
However, software based disaggregation, whether over a single server or across
multiple servers, has placed an increased burden on developers. They are compelled to
continuously adapt to new software stacks and migrate applications accordingly. In some
instances, despite the considerable porting efforts, the outcomes may not justify the in-
vestment. Unfortunately, much of the existing research fails to adequately address the
engineering investment challenge, instead prioritizing new software stacks primarily for
performance gains, albeit often at the expense of developer productivity.
This thesis focuses on improving developer productivity in software disaggregated
environments and advocates that unless a developer has evidence they should not have to
switch to a new software system or OS environment. Even when there is benefit for doing
so, software tools should be able to prioritize compatibility by leveraging advancements in
low-level system software stacks like the operating system and compilers.
We found initial evidence on ways to improve developer productivity in software
disaggregated systems by exploring analytical models backed with emulators to place bounds
on application performance. Our speedup models equip developers with a tool to decide
whether an application would benefit from resource disaggregation before actually trying to
use such a system. While analytical models help developers gain insight before adapting to
a new environment, developers may still have to port their applications to achieve high per-
formance. We found out through TrackFM that compilers can enable automatic porting of
applications with high performance, thereby improving developer productivity on memory
disaggregated systems. One of the limitations of TrackFM was that the runtime memory
policies had to be determined at static time for applications, which can lead to performance
overheads for certain applications. We overcome this problem by building CARDS, a sys-
tem that determines far memory policies proactively on software disaggregated systems
by combining compiler and runtime information for each data structure within an applica-
tion automatically. CARDS provides developers with a new alternative that determines far
memory polices dynamically instead of using a complex profiling based system to improve
policies. CARDS is built on top of TrackFM and overcomes the limitations of static com-
pilers by codesigning compiler analysis with the runtime which enables informed policy
decisions at data structure granularity.
The co-design of modern compiler analysis with runtime systems opens a unique
opportunity to create tools that enhance developer productivity within resource-disaggregated
architectures. We also envision that such codesign can be extremely helpful in emulation
of experimental hardware architectures to provide insights quickly without any application
porting effort. Leveraging my expertise in low-level system software, my thesis aims to ad-
vocate for the integration of automated tools in software disaggregated systems to prioritize
developer productivity in datacenter environments