The connection between our body and mind is integral in the way we perceive and relate to the world that exists around us. Our perceptions and emotional responses to those spaces can influence and become a powerful tool for design. In turn, architecture can encourage active and mindfullness in a person's everyday life. The architectural project is a mixed-use development consisting of a multi-family residence, hotel, coffee shop, and spa located off of 14th Street in the Columbia Heights neighborhood in Washington DC. The program provides spaces for dwelling, both temporary and permanent, to encourage both physical and psychological wellness. / Master of Architecture

A comparison of two control allocation methods is performed utilizing the F-15 ACTIVE research vehicle. The control allocator currently implemented on the aircraft is replaced in the simulation with a control allocator that accounts for both control effector positions and rates. Validation of the performance of this Moment Rate Allocation scheme through real-time piloted simulations is desired for an aircraft with a high fidelity control law and a larger control effector suite. A more computationally efficient search algorithm that alleviates the timing concerns associated with the early work in Direct Allocation is presented. This new search algorithm, deemed the Bisecting, Edge-Search Algorithm, utilizes concepts derived from pure geometry to efficiently determine the intersection of a line with a convex faceted surface. Control restoring methods, designed to drive control effectors towards a ``desired" configuration with the control power that remains after the satisfaction of the desired moments, are discussed. Minimum-sideforce restoring is presented. In addition, the concept of variable step size restoring algorithms is introduced and shown to yield the best tradeoff between restoring convergence speed and control chatter reduction. Representative maneuvers are flown to evaluate the control allocator's ability to perform during realistic tasks. An investigation is performed into the capability of the control allocators to reconfigure the control effectors in the event of an identified control failure. More specifically, once the control allocator has been forced to reconfigure the controls, an investigation is undertaken into possible performance degradation to determine whether or not the aircraft will still demonstrate acceptable flying qualities. A direct comparison of the performance of each of the two control allocators in a reduced global position limits configuration is investigated. Due to the highly redundant control effector suite of the F-15 ACTIVE, the aircraft, utilizing Moment Rate Allocation, still exhibits satisfactory performance in this configuration. The ability of Moment Rate Allocation to utilize the full moment generating capabilities of a suite of controls is demonstrated. NOTE: (02/2011) An updated copy of this ETD was added after there were patron reports of problems with the file. / Master of Science

The purpose of this research is to establish the effectiveness of tuned-mass-dampers (TMD) using semi-active magneto-rheological (MR) dampers to mitigate annoying floor vibrations. Annoying floor vibration is becoming more common in today's building structures since building materials have become stronger and lighter; the advent of computers has resulted in "paperless" offices; and the use of floors for rhythmic activities, such as aerobics and concerts, is more common. Analytical and experimental studies were conducted to provide an understanding of the effects of incorporating the semi-active-TMD as a remedy to annoying floor vibration. A pendulum tuned mass damper (PTMD) in which the tuning parameters could independently be varied was used. Closed form solutions for the response of the floor using passive dampers were developed. In addition, a numerical integration technique was used to solve the equations of motion where semi-active dampers are utilized. The optimum design parameters of PTMDs using passive and semi-active dampers were found using an optimization routine. Performances of the PTMD in reducing the floor vibration level at the optimum and when subjected to off-tuning of design parameters using passive and semi-active dampers were compared. To validate the results obtained in the analytical investigation, an experimental study was conducted using an 8 ft x 30 ft laboratory floor and a commercial PTMD. Comparative studies of the effectiveness of the PTMD in reducing floor vibrations using semi-active and passive dampers were conducted. / Master of Science

As farmers continue to get older, they will likely face age-related disabilities that impede their ability to work and increase risk of suffering serious injuries. One of the major age- related diseases is arthritis, which currently accounts for about 40% of disability cases in agriculture nationwide. The effect of arthritis on farmers is profound because it reduces their physical strength, joint range of motion and is a source of joint pain, all culminating in the lack of ability to perform routine activities regularly and safely. One way to decrease the rate of injuries is by reducing the strength and joint loading required to perform these activities through the use of wearable robotics. As opposed to existing solutions that focus only on injury prevention, this thesis will present an active, knee-assist exoskeleton intent on providing 30% of the necessary joint rotation force to perform activities such as sit-to- stand actions and the ascent/descent of stairs and hills. The device will be a lightweight, unobtrusive cable-driven exoskeleton actuated by distally-worn electric motors. We hope that use of the exoskeleton will result in increased ranges of motion and overall reduction of stress on the wearer's body, which will minimize the effects of arthritis and ultimately improve safety and quality of life. / Master of Science / As farmers continue to get older, they will likely face age-related disabilities that impede their ability to work and increase risk of suffering serious injuries. One of the major age-related diseases is arthritis, which currently accounts for about 40% of disability cases in agriculture nationwide. The effect of arthritis on farmers is profound because it reduces their physical strength, joint range of motion and is a source of joint pain, all culminating in the lack of ability to perform routine activities regularly and safely. One way to decrease the rate of injuries is by reducing the strength and joint loading required to perform these activities through the use of wearable robotics. As opposed to existing solutions that focus only on injury prevention, this thesis will present an active, knee-assist exoskeleton intent on providing 30% of the necessary joint rotation force to perform activities such as sit-to-stand actions and the ascent/descent of stairs and hills. The device will be a lightweight, unobtrusive cable-driven exoskeleton actuated by distally-worn electric motors. We hope that use of the exoskeleton will result in increased ranges of motion and overall reduction of stress on the wearer’s body, which will minimize the effects of arthritis and ultimately improve safety and quality of life.

Vehicle suspension systems play an integral role in influencing the overall performance of a vehicle. The suspension system of a vehicle performs multiple tasks, such as maintaining contact between the tires and the road and isolating the frame of the vehicle from road-induced vibration and shocks. A significant amount of research has been directed to improving the performance of the suspension system by varying the damping coefficient so as to alter the frequency response of the system. This study describes the development of such a damper. The goal of this research has been to design, model, fabricate and test a novel semi-active damper. The damper consists of two independent electronically controlled units placed in series with one another. The system was initially simulated using a 2 DOF quarter-car model and the performance characteristics of the damper were outlined. Following that, multiple design iterations of the damper were created and a MATLAB/Simulink model was used to simulate physical and flow characteristics of the damper. After the design and analysis was complete, the damper was fabricated and tested using a shock dyno at CenTiRe. The test results were then compared to the simulation results so as to confirm performance of the damper. Additionally, the results obtained on the dyno were then compared against that of a relative single semi-active and passive damper. / Master of Science

Active learning is a practical field of machine learning as labeling data or determining which data to label can be a time consuming and inefficient task. Active learning automates the process of selecting which data to label, but current methods are heavily model reliant. This has led to the inability of sampled data to be transferred to new models as well as issues with sampling bias. Both issues are of crucial concern in machine learning deployment. We propose active learning methods utilizing Combinatorial Coverage to overcome these issues. The proposed methods are data-centric, and through our experiments we show that the inclusion of coverage in active learning leads to sampling data that tends to be the best in transferring to different models and has a competitive sampling bias compared to benchmark methods. / Master of Science / Machine learning (ML) models are being used frequently in a variety of applications. For the model to be able to learn, data is required. Processing this data is often one of the most, if not the most, time consuming aspects of utilizing ML. One especially burdensome aspect of data processing is data labeling, or determining what each data point corresponds to in terms of real world class. For example, determining if a data point that is an image contains a plane or bird. This way the ML model can learn from the data. Active learning is a sub-field of machine learning which aims to ease this burden by allowing the model to select which data would be most beneficial to label, so that the entirety of the dataset does not need to be labeled. The issue with current active learning methods is that they are highly model dependent. In machine learning deployment the model being used may change while data stays the same, so this model dependency can cause for data points we label with respect to one model to not be ideal for another model. This model dependency has led to sampling bias issues as well; points which are chosen to be labeled may all be similar or not representative of all data resulting in the ML model not being as knowledgeable as possible. Relevant work has focused on the sampling bias issue, and several methods have been proposed to combat this issue. Few of the methods are applicable to any type of ML model though. The issue of sampled points not generalizing to different models has been studied but no solutions have been proposed. In this work we present active learning methods using Combinatorial Coverage. Combinatorial Coverage is a statistical technique from the field of Design of Experiments, and has commonly been used to design test sets. The extension of Combinatorial Coverage to ML is newer, and provides a way to focus on the data. We show that this data focused approach to active learning achieves a better performance when the sampled data is used for a different model and that it achieves a competitive sampling bias compared to benchmark methods.

Humans are designed to move. Movement is a key component of physical and mental maturation in children. It can take place in various settings, with different levels of intensity. During the developmental years of a child, it is imperative that a child is active. Most often movement and play are thought to occur outdoors. The idea of the"playground" activity does not have to be isolated to the outdoors. Children should be encouraged to be physically active in structured play, allowed free play with peers for social and emotional development, as well as learn through hands-on experiments that are important for their cognitive development. Play is how children experience their world and create new discoveries about themselves and others. This thesis will be explored through the design of an elementary school for Alexandria, VA. An elementary school creates the perfect setting for which these elements of movement and learning to combine. This thesis explores the way in which the movement of the outdoor school yard can occur within the school building. The school grounds serve as demonstration to the community for active learning. Incorporating active design through elevation changes, material changes and the transition between indoor and outdoor allow the school to be a model for "learning through movement." This school also begins to address the larger issues of our society's unhealthy lifestyle by designing three levels of active design for the community, building, and individual child. / Master of Architecture

The work presented in this thesis can be divided into two main subjects. First, lightweight designs for acoustic devices such as Helmholtz resonators and loudspeakers used for noise control in rocket payload compartments are developed. Second, active control using a hybrid control system (with structural and acoustic actuators) was tested experimentally. Due to the weight limitations for this application, Helmholtz resonators and loudspeakers are re-designed in order to reduce the device weight as much as possible while maintaining performance. For Helmholtz resonators, this is done by modeling the resonator for different structural shapes, wall materials and wall thicknesses using a finite element analysis software. The final design is then compared to the rigid resonators and is shown to perform effectively. These designs are then successfully applied to the full-scale fairing at Boeing facilities. In order to design a lightweight loudspeaker, a comparative approach was used. A standard 12' loudspeaker is taken as the reference loudspeaker and weight reduction solutions are applied to it while maintaining performance. The loudspeaker is characterized using mechanical, electrical and acoustical theories, and an optimization process is applied in order to minimize a defined cost function, which was taken as the total sound pressure output over a targeted frequency range per mass of the actuator. The results are used to build a lightweight loudspeaker together with a lightweight box, and the new designs are tested for comparison with the reference loudspeaker and shown to increase performance by 1.7 dB over 60-200 Hz band while reducing the mass by 78%. The second part of this thesis investigates the performance of a hybrid active control treatment featuring distributed vibration absorbers (DAVAs) and loudspeakers applied on a scale payload fairing. Several aspects such as causality, reference signals, and maximum controllable levels of this feedforward control scheme are the subjects of analyses. The results show that this active control approach can achieve significant amount of interior noise attenuation, and the total actuator weight required to control an external level of 138 dB can be reduced to 9.2kg using lightweight loudspeakers. However, it is shown that the attenuation levels can still be improved further by actuator positioning that gives more effective coupling of the actuators with the structural and acoustic modes and by using multiple references for the control system. / Master of Science

Annotating large unlabeled datasets can be a major bottleneck for machine learning applications. We introduce a scheme for inferring labels of unlabeled data at a fraction of the cost of labeling the entire dataset. We refer to the scheme as Bounded Expectation of Label Assignment (BELA). BELA greedily queries an oracle (or human labeler) and partitions a dataset to find data subsets that have mostly the same label. BELA can then infer labels by majority vote of the known labels in each subset. BELA makes the decision to split or label from a subset by maximizing a lower bound on the expected number of correctly labeled examples. BELA improves upon existing hierarchical labeling schemes by using supervised models to partition the data, therefore avoiding reliance on unsupervised clustering methods that may not accurately group data by label. We design BELA with strategies to avoid bias that could be introduced through this adaptive partitioning. We evaluate BELA on labeling of four datasets and find that it outperforms existing strategies for adaptive labeling. / Master of Science / Most machine learning classifiers require data with both features and labels. The features of the data may be the pixel values for an image, the words in a text sample, the audio of a voice clip, and more. The labels of a dataset define the data. They place the data into one of several categories, such as determining whether a image is of a cat or dog, or adding subtitles to Youtube videos. The labeling of a dataset can be expensive, and usually requires a human to annotate. Human labeled data can be moreso expensive if the data requires an expert labeler, as in the labeling of medical images, or when labeling data is particularly time consuming. We introduce a scheme for labeling data that aims to lessen the cost of human labeled data by labeling a subset of an entire dataset and making an educated guess on the labels of the remaining unlabeled data. The labeled data generated from our approach may be then used towards the training of a classifier, or an algorithm that maps the features of data to a guessed label. This is based off of the intuition that data with similar features will also have similar labels. Our approach uses a game-like process of, at any point, choosing between one of two possible actions: we may either label a new data point, thus learning more about the dataset, or we may split apart the dataset into multiple subsets of data. We will eventually guess the labels of the unlabeled data by assigning each unlabeled data point the majority label of the data subset that it belongs to. The novelty in our approach is that we use supervised classifiers, or splitting techniques that use both the features and the labels of data, to split a dataset into new subsets. We use bias reduction techniques that enable us to use supervised splitting.

This work investigates the use of multi-degree of freedom (MDOF) passive and active vibration absorbers for the control of structural vibration as an improvement to conventional single degree of freedom (SDOF) vibration absorbers. An analytical model is first used to compare passive two degree of freedom (2DOF) absorbers to SDOF absorbers using point impedance as the performance criterion. The results show that one 2DOF absorber can provide the same impedance at two resonance frequencies as two SDOF absorbers for equal amounts of total mass. Experimental testing on a composite cylindrical shell supports the assertion that a 2DOF absorber can attenuate two resonance frequencies. Further modeling shows that MDOF absorbers can utilize the multiple mode shapes that correspond to their multiple resonance frequencies to couple into modes of a distributed primary system to improve the attenuation of structural resonance. By choosing the coupling positions of the MDOF absorber such that its mode shape mirrors that of the primary system, the mass of the absorber can be utilized at multiple resonance frequencies. For limited ranges of targeted resonance frequencies, this technique can result in MDOF absorbers providing attenuation equivalent to SDOF absorbers while using less mass. The advantage gained with the MDOF absorbers is dependent on the primary system. This work compares the advantage gained using the MDOF absorbers for three primary systems: MDOF lumped parameter systems, a pinned-pinned plate, and a cylindrical shell. The active vibration absorber study in this work is highly motivated by the desire to reduce structural vibration in a rocket payload fairing. Since the efficiency of acoustic foam is very poor at low frequencies, the target bandwidth was 50 to 200 Hz. A 2DOF active vibration absorber was desired to exhibit broad resonance characteristics over this frequency band. An analytical model was developed to facilitate the design of the mechanical and electrical properties of the 2DOF active vibration absorber, and is supported by experimental data. Eight active vibration absorbers were then constructed and used in a multiple-input multiple-output (MIMO) feed-forward control system on a mock payload fairing under high level acoustic excitation. The results show significant levels of global attenuation within the targeted frequency band. / Master of Science