Upgrade of an experimental volumetric unit for gas adsorption equilibrium studies

In this work, a volumetric unit previously assembled by the research group was upgraded. This unit revamping was necessary due to the malfunction of the solenoid valves employed in the original experimental setup, which were not sealing the gas properly leading to erroneous adsorption equilibrium measurements. Therefore, the solenoid valves were substituted by manual ball valves. After the volumetric unit improvement its operation was validated. For this purpose, the adsorption equilibrium of carbon dioxide (CO2) at 323K and 0 - 20 bar was measured on two different activated carbon samples, in the of extrudates (ANG6) and of a honeycomb monolith (ACHM). The adsorption equilibrium results were compared with data previously measured by the research group, using a high-pressure microbalance from Rubotherm GmbH (Germany) – gravimetric. The results obtained using both apparatuses are coincident thus validating the good operation of the volumetric unit upgraded in this work. Furthermore, the adsorption equilibrium of CO2 at 303K and 0 - 10 bar on Metal-Organic Frameworks (MOFs) Cu-BTC and Fe-BTC was also studied. The CO2 adsorption equilibrium results for both MOFs were compared with the literature results showing good agreement, which confirms the good quality of the experimental results obtained in the new volumetric unit. Cu-BTC sample showed significantly higher CO2 adsorption capacity when compared with the Fe-BTC sample. The revamping of the volumetric unit included a new valve configuration in order to allow testing an alternative method for the measurement of adsorption equilibrium. This new method was employed to measure the adsorption equilibrium of CO2 on ANG6 and ACHM at 303, 323 and 353K within 0-10 bar. The good quality of the obtained experimental data was testified by comparison with data previously obtained by the research group in a gravimetric apparatus.

Scaling In-Memory databases on multicores

Current computer systems have evolved from featuring only a single processing unit and limited RAM, in the order of kilobytes or few megabytes, to include several multicore processors, o↵ering in the order of several tens of concurrent execution contexts, and have main memory in the order of several tens to hundreds of gigabytes. This allows to keep all data of many applications in the main memory, leading to the development of inmemory databases. Compared to disk-backed databases, in-memory databases (IMDBs) are expected to provide better performance by incurring in less I/O overhead. In this dissertation, we present a scalability study of two general purpose IMDBs on multicore systems. The results show that current general purpose IMDBs do not scale on multicores, due to contention among threads running concurrent transactions. In this work, we explore di↵erent direction to overcome the scalability issues of IMDBs in multicores, while enforcing strong isolation semantics. First, we present a solution that requires no modification to either database systems or to the applications, called MacroDB. MacroDB replicates the database among several engines, using a master-slave replication scheme, where update transactions execute on the master, while read-only transactions execute on slaves. This reduces contention, allowing MacroDB to o↵er scalable performance under read-only workloads, while updateintensive workloads su↵er from performance loss, when compared to the standalone engine. Second, we delve into the database engine and identify the concurrency control mechanism used by the storage sub-component as a scalability bottleneck. We then propose a new locking scheme that allows the removal of such mechanisms from the storage sub-component. This modification o↵ers performance improvement under all workloads, when compared to the standalone engine, while scalability is limited to read-only workloads. Next we addressed the scalability limitations for update-intensive workloads, and propose the reduction of locking granularity from the table level to the attribute level. This further improved performance for intensive and moderate update workloads, at a slight cost for read-only workloads. Scalability is limited to intensive-read and read-only workloads. Finally, we investigate the impact applications have on the performance of database systems, by studying how operation order inside transactions influences the database performance. We then propose a Read before Write (RbW) interaction pattern, under which transaction perform all read operations before executing write operations. The RbW pattern allowed TPC-C to achieve scalable performance on our modified engine for all workloads. Additionally, the RbW pattern allowed our modified engine to achieve scalable performance on multicores, almost up to the total number of cores, while enforcing strong isolation.