Model reduction in integrated controls-structures design

It is the objective of this paper to present a model reduction technique developed for the integrated controls-structures design of flexible structures. Integrated controls-structures design problems are typically posed as nonlinear mathematical programming problems, where the design variables consist of both structural and control parameters. In the solution process, both structural and control design variables are constantly changing; therefore, the dynamic characteristics of the structure are also changing. This presents a problem in obtaining a reduced-order model for active control design and analysis which will be valid for all design points within the design space. In other words, the frequency and number of the significant modes of the structure (modes that should be included) may vary considerably throughout the design process. This is also true as the locations and/or masses of the sensors and actuators change. Moreover, since the number of design evaluations in the integrated design process could easily run into thousands, any feasible order-reduction method should not require model reduction analysis at every design iteration. In this paper a novel and efficient technique for model reduction in the integrated controls-structures design process, which addresses these issues, is presented

Towards large-scale modelling of fluid flow in fractured porous media

To date, the complexity of fractured porous media still precludes the direct incorporation of small-scale features into field-scale modelling. These features, however, can be instrumental in shaping and triggering coarsening instabilities and other forms of emergent behaviour which need to be considered on the field-scale. Here we develop numerical simulation methods for this purpose and demonstrate their improved performance in single-and two-phase flow simulations with models of fractured porous media. Material discontinuities in fractured porous media strongly influence single-and multi-phase fluid flow. When continuum methods are used to model transport across such interfaces, they smear out jump discontinuities of concentration or saturation. To overcome this drawback, we “explode” hybrid finite-element node-centred finite-volume models along these introducing complementary finite-volumes along the material interfaces. With this embedded discontinuity discretization we develop a transport scheme that realistically represents the dependent variable discontinuities arising at these interfaces. The main advantage of this new scheme is its ability to honour the flow effects that we know that these discontinuities have in physical experiments. We have also developed a new time-stepping control scheme for the transport equation. It allows the user to specify the volume fraction of the model in which he/she is prepared to relax the CFL condition. This scheme is applied in a study of the impact of fracture pattern development on solute transport. These two-dimensional simulations quantify the effect of the fractures on macro-scale dispersion in geomechanically generated fracture geometries, as opposed to stochastically generated ones. Among other insights, the results indicate that fracture density, fracture spacing, and the fracture-matrix flux ratio control anomalous mass transport in such media. We also find that it is crucial to embed discontinuities into large-scale models of heterogeneous porous media

Time Domain Simulations of Arm Locking in LISA

Arm locking is a technique that has been proposed for reducing laser frequency fluctuations in the Laser Interferometer Space Antenna (LISA), a gravitational-wave observatory sensitive in the milliHertz frequency band. Arm locking takes advantage of the geometric stability of the triangular constellation of three spacecraft that comprise LISA to provide a frequency reference with a stability in the LISA measurement band that exceeds that available from a standard reference such as an optical cavity or molecular absorption line. We have implemented a time-domain simulation of arm locking including the expected limiting noise sources (shot noise, clock noise, spacecraft jitter noise, and residual laser frequency noise). The effect of imperfect a priori knowledge of the LISA heterodyne frequencies and the associated 'pulling' of an arm locked laser is included. We find that our implementation meets requirements both on the noise and dynamic range of the laser frequency.Comment: Revised to address reviewer comments. Accepted by Phys. Rev.

Robust eigensystem assignment for second-order estimators

An approach for the robust eigensystem assignment of flexible structures using full state or output feedback is developed. Using the second-order dynamic equations, the approach can assign the eigenvalues of the system via velocity and displacement feedbacks, or acceleration and velocity feedbacks. The eigenvalues and eigenvectors of the system are assigned, via the second-order eigenvalue problem for the structural system, in two steps. First, an orthonormal basis spanning the attainable closed-loop eigenvector space corresponding to each desired closed-loop eigenvalue is generated using the Singular Value or QR decompositions. Second, a sequential procedure is used to choose a set of closed-loop eigenvectors that are as close as possible to the column space of a well-conditioned target matrix. Among the possible choices of the target matrix, the closest unitary matrix to the open-loop eigenvector matrix appears to be a suitable choice. A numerical example is given to illustrate the proposed algorithm

The RNA-binding protein LARP1 is a post-transcriptional regulator of survival and tumorigenesis in ovarian cancer

RNA-binding proteins (RBPs) are increasingly identified as post-transcriptional drivers of cancer progression. The RBP LARP1 is an mRNA stability regulator, and elevated expression of the protein in hepatocellular and lung cancers is correlated with adverse prognosis. LARP1 associates with an mRNA interactome that is enriched for oncogenic transcripts. Here we explore the role of LARP1 in epithelial ovarian cancer, a disease characterized by the rapid acquisition of resistance to chemotherapy through the induction of pro-survival signalling. We show, using ovarian cell lines and xenografts, that LARP1 is required for cancer cell survival and chemotherapy resistance. LARP1 promotes tumour formation in vivo and maintains cancer stem cell-like populations. Using transcriptomic analysis following LARP1 knockdown, cross-referenced against the LARP1 interactome, we identify BCL2 and BIK as LARP1 mRNA targets. We demonstrate that, through an interaction with the 3 untranslated regions (3 UTRs) of BCL2 and BIK, LARP1 stabilizes BCL2 but destabilizes BIK with the net effect of resisting apoptosis. Together, our data indicate that by differentially regulating the stability of a selection of mRNAs, LARP1 promotes ovarian cancer progression and chemotherapy resistance

Identifying Influential Agents In Social Systems

This dissertation addresses the problem of influence maximization in social networks. In- fluence maximization is applicable to many types of real-world problems, including modeling contagion, technology adoption, and viral marketing. Here we examine an advertisement domain in which the overarching goal is to find the influential nodes in a social network, based on the network structure and the interactions, as targets of advertisement. The assumption is that advertisement budget limits prevent us from sending the advertisement to everybody in the network. Therefore, a wise selection of the people can be beneficial in increasing the product adoption. To model these social systems, agent-based modeling, a powerful tool for the study of phenomena that are difficult to observe within the confines of the laboratory, is used. To analyze marketing scenarios, this dissertation proposes a new method for propagating information through a social system and demonstrates how it can be used to develop a product advertisement strategy in a simulated market. We consider the desire of agents toward purchasing an item as a random variable and solve the influence maximization problem in steady state using an optimization method to assign the advertisement of available products to appropriate messenger agents. Our market simulation 1) accounts for the effects of group membership on agent attitudes 2) has a network structure that is similar to realistic human systems 3) models inter-product preference correlations that can be learned from market data. The results on synthetic data show that this method is significantly better than network analysis methods based on centrality measures. The optimized influence maximization (OIM) described above, has some limitations. For instance, it relies on a global estimation of the interaction among agents in the network, rendering it incapable of handling large networks. Although OIM is capable of finding the influential nodes in the social network in an optimized way and targeting them for advertising, in large networks, performing the matrix operations required to find the optimized solution is intractable. To overcome this limitation, we then propose a hierarchical influence maximization (HIM) iii algorithm for scaling influence maximization to larger networks. In the hierarchical method the network is partitioned into multiple smaller networks that can be solved exactly with optimization techniques, assuming a generalized IC model, to identify a candidate set of seed nodes. The candidate nodes are used to create a distance-preserving abstract version of the network that maintains an aggregate influence model between partitions. The budget limitation for the advertising dictates the algorithm’s stopping point. On synthetic datasets, we show that our method comes close to the optimal node selection, at substantially lower runtime costs. We present results from applying the HIM algorithm to real-world datasets collected from social media sites with large numbers of users (Epinions, SlashDot, and WikiVote) and compare it with two benchmarks, PMIA and DegreeDiscount, to examine the scalability and performance. Our experimental results reveal that HIM scales to larger networks but is outperformed by degreebased algorithms in highly-connected networks. However, HIM performs well in modular networks where the communities are clearly separable with small number of cross-community edges. This finding suggests that for practical applications it is useful to account for network properties when selecting an influence maximization method

A study on the sensitivity and simultaneous adjustment of a hoop-column antenna surface

The results of a recent surface adjustment of the 15-meter diameter hoop-column antenna are presented. A least-squares differential algorithm is used to adjust the surface shape as close as possible to a perfect parabola. Since the desired perfect parabola is not uniquely known a priori, parameters of the perfect parabola are included in the design vector along with the cable length changes. As an extension to an earlier study, lateral sensitivity is included in the least-squares adjustment procedure. In addition, the effect of cable length uncertainties on the surface RMS error is considered and an error bound is derived. The results in this study indicate an improvement over earlier studies. The sensitivity analysis provided a quantitative measure of the needed accuracy of the cable adjustments in the laboratory. Recommendations are included to further enhance shape adjustment

Novel Zwitterionic Copolymers to Enhance Hydrophilicity of PVDF Membranes: A Comprehensive Computational Study

Membrane technology covers all the engineering approaches with a key growth for large-scale industrial applications, including biotechnology, biomedical applications, food industry, and water and wastewater treatment. Poly (vinylidene fluoride) (PVDF) membrane has been gained remarkable attentions in recent years due to its excellent advantages in terms of thermal stability, chemical resistance, and high mechanical strength for water treatment. Despite its outstanding advantages, the performances of PVDF membranes are substantially limited by fouling problems. In this research study, we designed novel zwitterionic (ZW)-PVDF membranes with high hydrophilicity by employing a set of comprehensive computational methods. To achieve our goal, we first investigated the interactions occurring between water molecules and the fragments of hydrophobic and hydrophilic membrane models at the molecular level using the pair interaction energy decomposition analysis (PIEDA) as part of the fragment molecular orbital (FMO) method’s framework. This research direction is critical, since a research study of the reasons behind the interactions between water molecules and membrane materials would help design ground-breaking membranes with superior hydrophilicity. The computational studies and experimental analyses of PVDF and Polyacrylonitrile (PAN) membranes were considered as the models for hydrophobic and hydrophilic membranes, respectively. Density-functional theory (DFT), based on B3LYP functional and split-valance 6-311+G (d, p) basis sets, was used in order to optimize the geometry of PAN, PVDF, and their complexes with different numbers of water molecules. Furthermore, the functional groups of membrane surfaces were experimentally evaluated through Fourier-transform infrared spectroscopy (FTIR- ATR), 13C cross polarization magic angle spinning (13C CP MAS) Solid State Nuclear magnetic resonance SSNMR, and Fourier transform Raman (FT-Raman) spectroscopies. The confocal microscopic was also employed to interrogate water transport and the interactions between fluorescence particles through the membrane matrices. The non-covalent interactions in terms of electrostatic, exchange-repulsion, and charge-transfer parameters were comprehensively investigated for the designed ZW-PVDF copolymers. The performance of ZW moieties was derived from three different anionic groups in the ZW head, specifically, carboxylate, sulfonate, and phosphate. This approach was used in addition to the inclusion of a linker between the ZW head and the PVDF backbone, such as trimethyl ammonium groups and hydroxyl group, for an improvement of PVDF hydrophilicity. The quantum chemical calculations were conducted to examine the hydration structure of moieties. The interactions between the ZW moieties, with water molecules confirmed that it depended on the charged groups in addition to the chemical functional groups between charged groups. Furthermore, the types of anionic groups, the polar functional groups between charged groups, and the hydrophilic group, as a linker between charged groups of the ZW to the PVDF polymer backbone are the key reason for membrane hydrophilicity and the membrane water uptake. The double Zwitterionic PMAL®-C8-CB-OH-SB-PVDF was designed through the addition of protonated carboxyl group on a backbone of copolymer PMAL®-C8, and the protonated nitrogen atom of the amide group. This double zwitterion showed strong electrostatic interactions between individual water molecules and the secondary ammonium and the Oxygen of carboxybetaine, compared to PMAL®-C8-OH-SB-PVDF model. Our designed hydrophilic ZW-PVDF membranes, and especially the double zwitterion membrane, are an exciting development that can be applied in a broad range of water applications

Zeolites-Mixed-Matrix Nanofiltration Membranes for the Next Generation of Water Purification

Designing high performance and antifouling membranes are in a great need to remove water contaminations and to regulate the quality of drinking water. Mixed-matrix membranes (MMMs) could offer a solution to the permeability and selectivity trade-off in nanofiltration (NF) membranes. MMM could offer the physicochemical stability of a ceramic material while ensuring the desired morphology with higher nanofiltration permeability, selectivity, hydrophilicity, fouling resistance, as well as greater thermal, mechanical, and chemical strength over a wider temperature and pH range. Zeolites are fascinating and versatile materials, vital for a wide range of industries due to their unique structure, greater mechanical strength, and chemical properties. This chapter focused on zeolite-MMM for nanofiltration. Several key rules in the synthesis procedures have been comprehensively discussed for the optimum interfacial morphology between the zeolites and polymers. Furthermore, the influence of the zeolite filler incorporation has been discussed and explored for water purification. This chapter provided a broad overview of the MMM’s challenges and future improvement investigative directions