This paper describes a fast-time simulation designed to complement real-time human-in-the-loop simulations to support the design of terminal-area (TRACON) spacing and merging concepts. Fast-time simulations allow a variety of experimental conditions to be varied 'Monte Carlo-style.' Human performance models that represent flight crews and ATSPs simulate key interactions. Such simulations enable rapid, iterative concept refinement, and help focus subsequent human-in-loop simulations by identifying test scenarios and experimental conditions likely to provide clear insights. The paper presents preliminary fast-time simulation studies for TRACON spacing and merging concepts. The studies extend prior NASA ATM research, which has generally focused on increasing arrival efficiency (e.g., reducing vectoring) and throughput via ATM concepts that improve traffic flow predictability. In particular, the research has focused on trajectory-oriented operations, with greater information sharing and accompanying ATSP and flight deck automation tools. Following this general approach, the fast-time simulation results presented here principally address arrival scheduling and the ability to use automatically-computed speed adjustments to schedule deviations introduced by TRACON boundary metering fix arrival time and predicted landing speed errors for aircraft flying flight management system (FMS) routes to the runway. However, the paper also considers how this class of concepts relates to other ongoing ATM arrival concept research, the role of simulated agents (in particular, agent fidelity requirements for simulating increasingly refined concepts), and metrics for assessing concept efficacy in complementary real- and fast-time simulations. The remainder of the paper is organized as follows. It first describes the continuous-descent appro